Using structured communications to quantify social skills

ABSTRACT

Embodiments for using structured communications to quantify social skills and social behavioral factors. Communications between at least two devices are intercepted and/or relayed by a computer system wherein a portion of the communications correspond to an audible source and wherein the forwarding or processing of communications is based on a combination of historical, contextual and/or commanded information derived from current and past communications by the computer system. Primary statistics are measured based on the communications and contextual information. Secondary statistics are derived related to a user wherein the secondary statistics quantify social skills and behavioral factors of the user in one or more dimensions against one or more profiles or roles.

RELATED APPLICATIONS

This application is a continuation-in-part application of and claims thebenefit of co-pending patent application Ser. No. 13/401,146, entitled“OBSERVATION PLATFORM FOR USING STRUCTURED COMMUNICATIONS,” with filingdate Feb. 21, 2012, which is herein incorporated by reference in itsentirety.

The application with Ser. No. 13/401,146 claims priority to theprovisional patent application Ser. No. 61/445,504, entitled “Enabling aretail sales/service provider to interact with on-premise customers,”with filing date Feb. 22, 2011, which is herein incorporated byreference in its entirety. The application with Ser. No. 13/401,146 alsoclaims priority to the provisional patent application Ser. No.61/487,432, entitled “ACTIVITY COORDINATING ASSOCIATE'S AUTOMATICSERVICE ASSISTANT,” with filing date May 18, 2011, which is hereinincorporated by reference in its entirety.

This application is also a continuation-in-part application of andclaims the benefit of co-pending patent application Ser. No. 13/665,527,entitled “OBSERVATION PLATFORM FOR PERFORMING STRUCTUREDCOMMUNICATIONS,” with filing date Oct. 31, 2012, which is hereinincorporated by reference in its entirety.

This application is also a continuation-in-part application of andclaims the benefit of co-pending patent application Ser. No. 13/739,504,entitled “OBSERVATION PLATFORM FOR TRAINING, MONITORING, AND MININGSTRUCTURED COMMUNICATIONS,” with filing date Jan. 11, 2013, which isherein incorporated by reference in its entirety.

This application is also a continuation-in-part application of andclaims the benefit of co-pending patent application Ser. No. 13/832,944,entitled “OBSERVATION PLATFORM FOR USING STRUCTURED COMMUNICATIONS WITHCLOUD COMPUTING,” with filing date Mar. 15, 2013, which is hereinincorporated by reference in its entirety.

This application is also a continuation-in-part application of andclaims the benefit of co-pending patent application Ser. No. 13/833,572,entitled “MEDIATING A COMMUNICATION IN AN OBSERVATION PLATFORM,” withfiling date Mar. 15, 2013, which is herein incorporated by reference inits entirety.

BACKGROUND

Retailers are under constant pressure to cut costs, improve margins,improve customer service, increase floor traffic, and increase customersatisfaction. This has always been so, but the rise of the internet,available at home and while mobile, has increased the pressure greatly.Loyalty programs and per-customer pricing, such as special discounts,are one set of tools used in the past, and used more. Moreover, there isan increased demand to communicate efficiently with management,employees, customers and other associated with the retail environment.Such concerns also extend to situations and environments besides retailsettings. Modern communication devices provide for many communicationand business analytics opportunities in retail and other settings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a block diagram of an example environment for anobservation platform for structuring a communication in accordance withembodiments of the present technology.

FIG. 1B illustrates a block diagram of an example environment for anobservation platform for structuring a communication in accordance withother embodiments of the present technology.

FIG. 1C illustrates a block diagram of an example environment for anobservation platform for structuring a communication in accordance withother embodiments of the present technology.

FIG. 1D illustrates a block diagram of an example environment for anobservation platform for mediating a communication in accordance withother embodiments of the present technology.

FIG. 1E illustrates a block diagram of an example environment for anobservation platform for structuring a communication with cloudcomputing in accordance with other embodiments of the presenttechnology.

FIG. 2 illustrates a block diagram of an example environment forstructuring communication in an observation platform in accordance withembodiments of the present technology.

FIG. 3 illustrates a flowchart of an example method for structuringcommunication in an observation platform in accordance with embodimentsof the present technology.

FIG. 4 illustrates a flowchart of an example method for discipliningcommunications in accordance with embodiments of the present technology.

FIG. 5 illustrates a flowchart of an example method for observing andrecording users of communication devices in accordance with embodimentsof the present technology.

FIG. 6 illustrates a flowchart of an example method for characterizingcommunications in a group of users in accordance with embodiments of thepresent technology.

FIG. 7 illustrates a flowchart of an example method for structuringcommunication in a plurality of observation platforms in accordance withembodiments of the present technology.

FIG. 8 illustrates a flowchart of an example method for performingcommunications in an of observation platforms in accordance withembodiments of the present technology.

FIG. 9 illustrates a flowchart of an example method for performingcommunications in an of observation platforms in accordance withembodiments of the present technology.

FIG. 10 illustrates a flowchart of an example method for performingcommunications in an of observation platforms in accordance withembodiments of the present technology.

FIG. 11 illustrates a flowchart of an example method for performingcommunications in an of observation platforms in accordance withembodiments of the present technology.

FIG. 12 illustrates a flowchart of an example method for performingcommunications in an of observation platforms in accordance withembodiments of the present technology.

FIG. 13 illustrates a flowchart of an example method for structuredtraining in an observation platform in accordance with embodiments ofthe present technology.

FIG. 14 illustrates a flowchart of an example method for monitoringcommunications in an observation platform in accordance with embodimentsof the present technology.

FIG. 15 illustrates a flowchart of an example method for mining data inan observation platform in accordance with embodiments of the presenttechnology.

FIG. 16 illustrates a flowchart of an example method for mining data inan observation platform in accordance with embodiments of the presenttechnology.

FIG. 17 illustrates a flowchart of an example method for mediating acommunication in an observation platform in accordance with embodimentsof the present technology.

FIG. 18 illustrates a flowchart of an example method for mediating acommunication in an observation platform in accordance with embodimentsof the present technology.

FIG. 19 illustrates a flowchart of an example method for usingstructured communications to quantify social skills in accordance withembodiments of the present technology.

FIG. 20 illustrates a flowchart of an example method for usingstructured communications to validate a hypothesis related to socialskills in accordance with embodiments of the present technology.

FIG. 21 illustrates a flowchart of an example method for using anobservation platform to measure and quantify social skills in accordancewith embodiments of the present technology.

FIG. 22 illustrates a flowchart of an example method for using anobservation platform to measure and quantify social skills in accordancewith embodiments of the present technology.

The drawings referred to in this description of embodiments should beunderstood as not being drawn to scale except if specifically noted.

DESCRIPTION OF EMBODIMENTS

Reference will now be made in detail to embodiments of the presenttechnology, examples of which are illustrated in the accompanyingdrawings. While the technology will be described in conjunction withvarious embodiment(s), it will be understood that they are not intendedto limit the present technology to these embodiments. On the contrary,the present technology is intended to cover alternatives, modificationsand equivalents, which may be included within the spirit and scope ofthe various embodiments as defined by the appended claims.

Furthermore, in the following description of embodiments, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present technology. However, the present technologymay be practiced without these specific details. In other instances,well known methods, procedures, components, and circuits have not beendescribed in detail as not to unnecessarily obscure aspects of thepresent embodiments.

Unless specifically stated otherwise as apparent from the followingdiscussions, it is appreciated that throughout the present descriptionof embodiments, discussions utilizing terms such as “receiving,”“intercepting,” “measuring,” “recognizing,” “deriving,” “storing,”“relaying,” “executing,” “generating,” “determining,” “tracking,”“recording,” “identifying,” “making,” “sending,” “tracking,”“monitoring,” “mining,” or the like, refer to the actions and processesof a computer system, or similar electronic computing device. Thecomputer system or similar electronic computing device, such as atelephone, smartphone, smartphone in conjunction with a Bluetoothperipheral, or handheld mobile device, manipulates and transforms datarepresented as physical (electronic) quantities within the computersystem's registers and memories into other data similarly represented asphysical quantities within the computer system memories or registers orother such information storage, transmission, or display devices.Embodiments of the present technology are also well suited to the use ofother computer systems such as, for example, optical and mechanicalcomputers.

Overview of Using Structured Communications to Measure and QuantifySociability Skills

Embodiments of the present technology are for using structuredcommunications to measure and quantify sociability skills. This may beaccomplished using an observation platform that may involve a number ofusers, people or other computer systems and provides structured anddisciplined communications for the users using devices and captures dataregarding the communications and devices such as performance metrics andPrimary Statistics. The present technology may be employed in variousenvironments such as retail settings, public-stage floors, outdoorvenues, concerts, police scenarios, disaster areas, schools, sportingevents, hospitality operations, security operations, militaryoperations, a prison organization, customer service, manufacturingorganization, a factory, and other environments where humans worktogether and where communications occur between users and or computersystems.

Employees typically establish or have an informal social network made upof other teammates who can share talents and/or enthusiasm, provideneeded help and/or answer questions, or assist when trying to solveproblems. The social network found in retail stores is often dynamic dueto the constant inflow and outflow of employees, is inherentlyself-organizing and is typically not company implemented, and istypically difficult to document, measure, or quantify. As a retailstore's social network matures and evolves, certain employees oftenemerge as influential or “go to people” who can be counted on whensomeone, such as an employee or a customer, needs help or a task needsto be done. Having these “go-to” people on a shift can make or break astores performance, thus making these people valuable to an enterprise.Other employees take up roles such as “teachers” or “mentors,”“task-doers” or “helpers” for the go-to people.

An employee's past work experience alone is not the leading indicator ofwhether or not the employee is influential or a “go-to” person in theparticular retail setting. To achieve this informal status, the employeenot only needs to be viewed as having the knowledge that others need,but they also need to have other factors such as being approachable,being positive in attitude and actions, and/or socially available andresponsive for customers and employees to engage with them. These otherfactors may be described as sociability factors, sociability potential,or social skills. Managers in the retail setting may be able todetermine or measure the employee's experience through their length ofservice or subject expertise, but when it comes to the sociabilityfactors or social skills, managers have few tools with which to measure,quantify or evaluate and compare an employee's effectiveness other thansubjective anecdotal or gut feelings. Consequently, when managers aretransferred or quit, this learned anecdotal knowledge often leaves withthem and an incoming manager has to learn the behavioral patterns fromscratch. It is also challenging to measure sociability factors inprospective employees during the new hire process and probationaryperiod.

The present technology operates by using an observation platform,devices and structured communications from which to gather or collectPrimary Statistics that may be used to generate Secondary Statistics.The Primary Statistics and Secondary Statistics are utilized as a partof an assessment of the sociability factors, social skills, orsociability potential, of a user in the observation platform. Theassessment may be used by a manager, others, or computer systems to makedecisions for combining groups into teams or for the obtaining of othergoals. The present technology may be to run continuous assessments ofpeople skills, including the dependency on context, and then to use theassessments to guide planning, discover causes, provide training, andmake the management task more effective. The present technologyintroduces the concept of quantifiable ‘Sociability Scoring,’ and theprofit-making potential of employing measured sociability scores to thetraining, deployment, alignment, assessment and management of storepersonal. It should be appreciated that the present technology mayextend to other environments besides a retail setting wherever it isuseful to organize humans into groups depending on their social skills.Sociability scores may also be described as social engagement quotientand are quantified metrics, which may convey the ability and willingnessof a person to communicate, educate, and engage with others.

The present technology uses the observation platform to intercept acommunication from a first device at a computer system and relay thecommunication to a second device or second computer system where thefirst computer system determines the relayed destination by derivingcontext information from the communication and/or stored data relevantto the communication. The first computer system measures or collectsPrimary Statistics related to the devices, the communication and thecomputer systems. The Primary Statistics can be then used to generateSecondary Statistics to generate or create an assessment of a userassociated with the device. The primary and Secondary Statistics andassessment are the quantified social score of the user. The assessmentis then made available to a manager, others or a computer system for usein creating groups or teams or assessing an employee's capabilities,performance or alignment with the company's goals. For example, themanager may create a work schedule of employees using the assessment toensure that a “go-to” person is scheduled for each shift. Thus thepresent technology may be used to measure or quantify sociability scoresof employees and make that information available for managers, others ora computer system to use in making decisions.

DEFINITIONS

Sociability Score: Quantified metrics that conveys the ability andwillingness of a person to communicate, educate, or engage with others.May also be referred to as Social Engagement Quotient (SEQ), SocialQuotient (SQ), social skills, people skills, social factors, or socialpotential.

Primary Statistics: Those numerical observations that can be obtained bythe observation platform from direct use of any and all of itscommunication-mediating, location-sensing powers and context informationgathering. The primary statistical data may include, but not limited tosuch directly measurable quantities such as: engaged or availabletime(s), locations, locations traversed including speed and direction,listen time, talk time, number of listeners, geographic location of thespeakers and listeners, type of communication (e.g., broadcast, privateconversations, interruptions, group conversations, announcements,interrupting announcements, mandatory response messages), length of thecommunication session, initiator of communications, receiver ofcommunications, presence information, keywords spoken or listened to,tone of voice, speech cadence, banter rate, emotion and inflection (asmeasured by voice stress analysis tools), lengths of speech segments,what policies are used for the communications, when and where two ormore individuals dwell in close proximity to each other or to specificlocations, the speed of movement and pausing of the listeningindividuals during/after talking or listening, the frequency thatlisteners delay hearing a message or drop out from what a speaker issaying, and/or promptness of responses to what was heard, InertialMeasurement Unit (IMU) data, radio signal strength (RSS), signal tonoise ratio (SINR), measurements from accelerometer, and (X,Y,Z)location coordinates. Note that many of these items are fundamentallystatistical. These items may also be referred to as first order data andmetrics, primary observation, primary metrics, or primarycharacteristics.

Secondary Statistics: Those numbers generated through the application ofinference rules or combinatorial rules from the Primary Statistics.These items may also be referred to as second order data and metrics,secondary observations, secondary metrics, or secondary characteristics.Contextual information may be derived from Secondary Statistics may beused for determination of message flow and therefore be part of theoverall metadata referred to below.

Big data techniques: big data techniques.

Social graphs: Presentations of data or visual representations showingnumerical or causal inter-relationships, i.e., lines of varying densityconnecting names to indicate the intensity of communications orstrengths of relationships, interactions or engagements.

Inference rule: A specific algorithmic procedure for processing aspecified set of input data to produce a specified set of output data.At the simplest, the procedure may be to construct a weighted sum of theinputs to produce a single output number. May also be referred to ascombinatorial rule.

Higher-order statistic: Those numbers generated through the applicationof Inference rules or combinatorial rules from the Primary Statistics orSecondary Statistics. May also be referred to as higher-orderobservation or higher-order metrics.

Store performance data: Goals and results, expressed as metrics ornumbers, that comprise both a specification of what is important intargeted performance and that also contain historical data which can beuseful in learning about what seems to matter, either through humaninsight or intuition, or through machine-learning via an algorithmicprocedure. May also be referred to as outcome data or desiredobjectives.

Validated: Inference rules that have been proved to have a useful andmeaningful correlation to desired objectives by comparing the higherorder statistics that they generate to those objectives. Also, thoseinference rules where the strength of the weights or the size of theother numerical values in the rule are adjusted to optimize the observedcorrelation. May also be referred to as verified.

External statistics: Those numerical observations that are useful ingenerating Secondary Statistics or higher-order statistics but that comefrom outside the scope of the observation platform. One example is thegross sales receipts from a cash register which might be tiedstatistically to circumstances visible to the observation platform viaan observed basket identification. A second example would be somemeasurement of shopper locations by an external smartphone application.May also be referred to as external observations.

Modeling: Using either the verified or tuned Inference rules or theemployee and team behavioral metrics as inputs to a business model inorder to calculate a modeled result corresponding to the desiredobjectives. May also be referred to as forecasting.

Human-generated hypothesis: Inference rules guessed by ‘common-sense’ orexpert opinion, possibly followed by a tuning step using comparison withhistorical data. May also be referred to as expert-generated hypothesisor expert-generated relationship

Machine-generated inference rule: Inference rules generated at least inpart by an algorithmic procedure, and then tuned to validate andoptimize the observed correlation to objectives. May also be referred toas machine-generated hypothesis or machine-generated relationship.

Overview of an Observation Platform

The present technology employs an observation platform for structuredcommunications and for gathering or collecting Primary Statistics. Thefollowing overview describes how an observation platform is used forcommunications between devices and computer systems and is used forcollecting Primary Statistics from devices, communications and computersystems. Individual details, embodiments, and components of theobservation platform described herein may or may not be used forembodiments pertaining to using observation platform to measure andquantify social skills.

Using structured communications in an observation platform, as referredto herein, may refer to the following actions regarding communicationsbetween two or more users or one user and one or more computer systems:mediating, disciplining, structuring, controlling, participating,discouraging, encouraging, influencing, nudging, making an example of,permitting, managing, managing to be in compliance with policies,measuring what goes on as a communication occurs, characterizing,enabling, observing, recording, correcting, directing, etc.

The mediating, structuring or disciplining process envisioned hereininvolves using a communications and computer system as a platform toreceive communications from users, devices and computer systems, togenerate or parse metadata related to the communication, and to relaythe communication based on the metadata. Communications are enabled bymultiple means including: simply speaking names, questions or commands;press-to-talk broadcasting to everyone, groups or locations; listeningto pre-established information (e.g., podcasts or info-casts), movinginto locations where information is presented or requested, informationfrom other users on the system, or information from other systems orprocesses within this system related to actions required or informationnecessary. The system, including other users, may prompt users forverbal contributions to the data store or seek selected button pressesto determine further context or supplemental information and actions ofthe user. In conjunction with the communications and signalinginformation being exchanged, the system collects other relevant datawhich may include signals or sounds useful for location determination,sounds useful for system optimization or user environment detection, orother signal information (audible or visual) relevant to operating inthe desired coverage space.

One purpose of structuring or disciplining a communication is forassociates to become more productive and more effective customer serviceassociates or sales people in a retail setting. The present technologymay accomplish this goal by monitoring communications of the users thatoccur via communication devices. The communications may be monitored toderive context information from the communication such as the name ofthe user, geographic location of a user, the state or status of the user(e.g., busy, available, engaged, conversing, listening, out-of-range,not logged on, etc.), business metrics regarding the user's interactionwith others, and commands from the user. The communications may bemonitored by a computer system associated with a radio base station thatacts as a central hub for the user communications. The computer systemmay convert audible, voice or speech communications to a text ormachine-compatible format using standard and well-known techniques. Thetext may be used to derive the context information from thecommunication. The computer system may also store some or all of thecommunication including the time and geographic location of the device,the audible portion of the communication and the text format of thecommunication. The structured communications may extend beyond a singlevenue to multiple venues or storage locations without regard togeographic location. Customers or users may refer to customers who arepurchasing items in an environment, past customers, potential customers,perspective customers, shoppers, browsers, or others who enter theenvironment and do not represent the environment in an official capacitysuch as an employee does.

In one embodiment, the computer system generates or parses metadatarelated to a communication and also knows metadata for each of aplurality of devices in the observation platform. The computer system isthen able to match an attribute of the metadata from the communicationto an attribute from the metadata of at least one of the plurality ofdevices in the observation platform. The communication may then beforwarded to the matched device. The metadata may be described asattributes, tags, or characteristics of a communication. Thecommunication may be a signal generated by user device and may comprisespeech, text, audio, video, or a combination thereof. The attributes ofthe metadata may not be associated with the content of the signal andare related to context of the signal such as the time the signal wassent, an identification of the device that sent the signal, a locationof the device when the signal sent, a geographic zone the device islocated in, history of the device sending communication, etc. In oneembodiment, the metadata is associated with the content of the signal,such as text. The generating of metadata and relaying of thecommunication may occur substantially in real time such that a user ofthe device does not perceive any delay in communications.

In one embodiment, the computer system uses the derived contextinformation to determine a destination of the communication and forwardsor relays the communication to the destination. For example, a firstuser may attempt to contact a second user via communication devices. Thefirst user sends the communication to the computer system associatedwith the radio base station. The computer system recognizes the firstuser and is able to derive context information regarding thecommunication and determine that the communication's destination is athird user. The computer system then relays the communication, via theradio base station, to a communication device associated with the thirduser. The computer system may also convert the communication to text andderive contextual or performance metrics regarding the first or thirduser. For example, the first user may be an associate in a retailsetting and the third user is a customer. The first user may beresponding to a query made by the third user. The performance metric maybe the length of time it took for the first user to respond to the queryor may be whether or not the query was satisfied or may be a differentmetric entirely. The computer system may derive and store more than oneperformance metric. The computer system may also access more than onecommunication regarding a user to determine some metrics.

In one embodiment, the computer system uses the derived contextinformation to determine a destination of the communication and forwardsor relays the initial communication to the destination. For example, afirst user may attempt to contact a second user via communicationdevices. The first user sends the communication to the computer systemassociated with the radio base station. The computer system recognizesthe first user and is able to derive context information regarding thecommunication and determine that the communication's destination is athird user or plurality of users. The computer system then relays thecommunication, via the radio base station, to a communication deviceassociated with the third user or said plurality of users. The computersystem may then instruct the device of the first user to communicatedirectly with the device(s) of the third or plurality of users for theduration of the conversation. The computer system will continue toobserve the communications and will continue to derive contextual andperformance information from all connected devices. Additionally, thecomputer may instruct direct communications between a plurality ofdevices depending on context and other meta-information,

In one embodiment, the computer system is able to determine the state ofthe user based on either direct user action such as a button press orvoice command; or based on inference from words being spoken, motions,locations or other contextual information. In one embodiment, the thirduser may be out of range of the radio base station and sendscommunications via a network associated with the computer system. In oneembodiment, the third user may be part of a similar operation to that inFIG. 1A, i.e., another retail outlet or corporate headquarters for thesame company in a different location as shown in FIG. 1C.

In one embodiment, the first computer system that receives the signaldoes not perform all of the functions of the present technology, butinstead relies on cloud computing to perform some of the functions. Forexample, the first computer system may receive the signal and thenforward it to a second computer system. The second computer system maythen derive context information from the signal and determine adestination for the signal. The destination may be one or morecommunication devices that may or may not be within radio range of theradio base station associated with the computer system. The contextinformation and destination may then be sent to the first computersystem. The second computer system may also store data associated withthe observation platform such as signal logs, the signals themselves, orspeech-to-text conversions of the signals. In one embodiment, the secondcomputer system is not physically proximate to the first computer systembut is connected via a network. In one embodiment, the second computersystem is a plurality of computer systems that may be a peer-to-peernetwork, a server farm, computers used for cloud computing, or acombination thereof.

In one embodiment, the computer system is able to determine geographiclocations of users based on information received from devices associatedwith the users. The geographic location data may be stored as dataassociated with a user's communications device at a particular time, oras a performance metric, or may be combined with other information togenerate a performance metric. The geographic information may also beused by managers or others to mentor or train associates or others tooptimize customer service.

A user, as referred to herein, may be a person or people such as,associates, employees, managers, trainees, trainers, customers,suppliers, vendors, emergency responders, personnel, etc. In oneembodiment, the user interfaces with a device for communications withother users. Such a device may be a handheld device, a wearable device,a headset, a smartphone, an earpiece, a radio, a computer system, orother device capable of providing communications between users. Suchusers may be external to the operating entity and desire access viasmart devices or applications.

A performance metric may also be a metric, a key performance indicator(KPI) or a business metric. A metric or performance metric as referredto herein may be any type of data associated with or derived from acommunication between users, including the location of thecommunications device, buttons pressed, or the words spoken and thecontextual state at the time of a particular communication event. In oneembodiment, the computer system is able to generate a visualrepresentation of metrics. For example, the visual representation may bea map of the geographic location of the users in an environment or mayvisually demonstrate the status or activities of a user. In anotherexample, the visual representation may be textual information such asthe number of communications sent by a user or the length of time ittook for a user to respond to a communication or move to a specificlocation. The performance metrics may be sent or displayed to a manageror other user for use in making decisions. The performance metrics maybe used by the manager, others, or a computer system to optimizecustomer service in a retail setting by taking actions such asreprimanding or rewarding an associate or measuring who responds and thetime it takes to open a new register based on a request from a person orother input signal to the system. Performance metrics may also generatereal-time alarms or notifications that action or coordination is needed.

The present technology provides for many examples of how structuringcommunications may be used in various environments for a variety ofpurposes. The following discussion will demonstrate various hardware,software, and firmware components that are used with and in computersystems and other user devices for structuring communications usingvarious embodiments of the present technology. Furthermore, the systems,platforms, and methods may include some, all, or none of the hardware,software, and firmware components discussed below.

Using Structured Communications to Quantify Social Skills

With reference now to FIG. 1A, a block diagram of an environment 100 fortraining, monitoring, and mining communications in an observationplatform. Environment 100 includes devices 105, 110 and 130, radio basestation 115, computer 120, database 125 and network 135. Environment 100comprises components that may or may not be used with differentembodiments of the present technology and should not be construed tolimit the present technology. Some or all of the components ofenvironment 100 may be described as an observation platform forstructuring a communication.

The present technology makes use of communication devices. Radio basestation 115 and devices 105, 110 and 130 may also be described ascommunication devices. Devices 105, 110 and 130 may be user devices thatare mobile and employed by a user to communicate with other users viaother devices. Communications between the devices may be described assignals. A communication may be sent using a single signal or aplurality of signals. For example, a first signal of the communicationmay pertain to an audible source and a second signal pertains toinformation indicative of geographic information. The first and secondsignal may be related to one another as part of the same overallcommunication, or the signals may not be inherently related to oneanother. The devices 105, 110 and 130 may be a smartphone, a personaldigital assistant, a fob, a handheld device, a headset device or othersmall electronic device. In one embodiment, devices 105, 110 and 130employ speakers and microphones with control buttons for audiblecommunications and/or LEDs or screens for visual information. Thecontrol buttons may be pressed as signal buttons, push to talk buttons,volume control buttons, and power on/off buttons or other standardbuttons and may be options on a touchscreen. Devices 105, 110 and 130may be handheld, may be worn around the neck, and may be a headset wornon the head or behind the ear or otherwise interfaced with the humanbody. Devices 105, 110 and 130 may or may not comprise a screen ordisplay such as a liquid crystal display (LCD). In one embodiment,devices 105, 110 and 130 do not comprise a display such that a user isnot inundated with too many options or too much information from thedevice. A user device without a display may simplify communications andthus allow heads-up awareness and presence in the environment. Anotheruser, such as a customer or vendor/supplier, may be more likely toemploy the device for its intended purpose if the human interface issimplified.

Devices 105, 110 and 130 and other devices in environment 100 may bedispensed to a user upon entering environment 100 or may be brought bythe user into environment 100. For example, in a retail setting,associates may be issued devices by the employer or owner of theretailer setting. Customers in the retail setting may also be offered orissued devices as they enter or traverse the retail setting. Customersmay choose whether or not to accept the device or whether or not to usethe device after accepting it. The associate devices and the customerdevices may or may not be the same type or model of devices.Alternatively, the customer may bring a device into the retail settingsuch as a smartphone. An application on the customer's smartphone willallow the customer to use the device for communications in the storewith associates or others in accordance with present technology. Thecustomer may remain anonymous or may elect to identify themselves. Inone embodiment, recognition of the customer's identity is not requiredfor additional services or offers.

Devices 105, 110 and 130 may be low power devices. The devices may usebatteries or solar power including either ambient or battery solar powerin a low duty-cycle manner to save power. In one embodiment, the deviceshave an automatic sleep function when location of the device does notchange and no communications are sent or received after a period oftime.

Radio base station 115 may be a communication device that is capable ofcommunicating with devices 105, 110 and 130. Radio base station maysimply be a component of computer 120 or may be a standalone device thatis coupled with, connect to, or otherwise associated with computer 120.Radio base station 115 and computer 120 may be physically adjacent toone another or may be separated by a distance (e.g., cloud services).Computer 120 is able to receive communications from radio base station115 and to send communications to radio base station 115 for radio basestation 115 to transmit the communication to its destination. Computer120 is a computer system with a process and memory and is capable ofexecuting commands, software and firmware. Computer 120 may be a desktopcomputer, a server computer, a cloud-based computer or other standardcomputing system or may be custom built for the present technology.

Radio base station 115 and devices 105, 110 and 130 employ standardtechniques for communicating wirelessly. The communications may beperformed using radio techniques such as near field communications,short wave radio, infrared, Bluetooth, Wi-Fi, standard wireless computernetwork protocols, etc. Devices 105, 110 and 130 may be able tocommunicate with each other directly or through radio base station 115.Devices 105, 110 and 130 communicate with each other under the controlof the computer system 120. In one embodiment, all communications inenvironment 100 are relayed through radio base station 115 which acts asa central hub. For example, device 105 may communicate with device 110by device 105 sending a communication to radio base station 115,computer 120 derives that device 110 is the destination for thecommunication and relays the communication to device 110. This may occurautomatically and quickly enough such that the users will not experienceany undue lag in communications. In one embodiment, devices 105, 110 and130 may communicate directly with computer 120. For example, a user mayissue a command to computer 120 via device 105 or computer 120 may sendinformation to device 105. Information sent from computer 120 to device105 may be an audible voice signal or may be textual, contextual,geographical or graphical data to be displayed at device 105, if it isproperly equipped to do so.

In one embodiment, devices 105, 110 and 130 may communicate with oneanother directly, and their signals may be monitored and processed bycomputer system 120 via a monitoring system associated with the radiobase station 115. Instructions or commands may still be directed towardsthe computer system 120.

In one embodiment, computer 120 is able to recognize a user sending acommunication. The user may be recognized based on the device used tosend the communication to computer 120 and radio base station 115. Forexample, device 105 may have a unique signature associated with itstransmissions such that computer 120 can identify differentiate thedevice from another user. Such recognition of a user may then beemployed by computer 120 for future communications with other devices.In one embodiment, the signal or communications between devices areencrypted. The signal may be encoded such that it is unique to aspecific device. The encryption or encoding may be employed by computer120 to recognize the user of the device. In one embodiment, the user mayidentify himself to the computer system 120 and the computer system 120makes the association between user identification and device 105'sinternal electronic identification.

Computer 120 may determine that the destination of a communication is asingle device or a plurality of devices. Thus computer 120 may relay acommunication from device 105 only to device 110 or may relay it to bothdevice 110 and device 130. Computer 120 may determine that another userdevice is the destination of a communication originated by device 105but may also directly respond to the communication by executing acommand or sending a communication back to device 105. In oneembodiment, a communication from device 105 has more than onecharacteristic or aspect. For example, the communication may have afirst characteristic that corresponds to an audible source such thewords spoken by a user employing device 105. The communication may alsocontain contextual information such as engaged, available, listening toinformation, communicating in a conversation, out-of-range, returning tocoverage zones, or other behavioral/contextual information. Thecommunication may also have a third characteristic that comprisesgeographical position information of device 105 or may have informationindicative of a geographic position of device 105. Computer 120 is ableto determine a geographic position and direction of motion of a devicefrom the information indicative of a geographic position of device. Themotion may also be described as path of travel. A characteristic of thecommunication may be a portion of the communication, data associatedwith the communication, attributes of the communication, or metadataregarding the communication.

In one embodiment, computer 120 comprises a storage medium for storingsome or all of a communication. Computer 120 may store allcommunications between devices in environment 100. Computer 120 maystore communications for a pre-determined amount of time or based onother characteristics such as user, location or types of communications.Different characteristics of the communication may be stored includingportions of the communication itself. Additionally, the computer mayrequest and store all audible information regardless if the user pressesa push to talk button or otherwise signals the need to begin acommunication. For example, the communication may comprise an audibleportion, a text portion, information indicative of a geographicalposition, and a geographical data portion. The audible portion may alsobe converted to text. Computer 120 may store all or some of thedifferent portions including the portion converted to text. Computer 120may store geographic position information regarding a device over aperiod of time such that a path of travel or speed/direction of the usermay be inferred. Thus the position and context of a user may be mapped,tracked or predicted through a physical environment or area.

In one embodiment, computer 120 receives a communication from a devicewith a portion of the communication that corresponds to spoken words ofthe user of the device. Computer 120 is able to convert the spoken wordsportion to information used by computer 120 to derive contextinformation from the communication to determine performance metricsregarding the communication or the user of the device. The resultinginformation may also be interpreted as a command for computer 120 toexecute. The resulting information may also be employed to determine adestination for the communication or to trigger an automated responsefrom the system using stored or external information.

In one embodiment, each speaker is identified with a unique identifierwith each voice file so that a speech recognition engine can train onthe speaker's voice and more accurately choose words from thedictionaries and individual user grammars. Individually customizeddictionaries and grammars may be used for the sequential context of thespoken words. For example, saying, “urgent Bob” is interpreted bylooking up the first word in a command dictionary and the second word ina names or places dictionary. In one embodiment, a frequency table isbuilt for each user defining how frequently they call a name or place toimprove the probability of selecting the correct word. In oneembodiment, if a command, name, or place is not understood, the systemmay default to the most likely destination group. The user can easilyopt out of the default destination and start again. Alternatively, ifthe command, name or place is not recognized, the computer system 120may be programmed to default to a simple reply such as “please sayagain” or “person not found.”

In one embodiment, computer 120 executes a command received from device105. The command may be directly received from device 105 or may bereceived in an audible voice signal which is converted to text and theninterpreted to be a command for computer 120. The command may be toinitiate a virtual voice connection between device 105 and device 110.The command may be to initiate a connection to a telephony system suchthat a user of device 105 may communicate with another user who isemploying a telephone for communication. The command may be for computer120 to store information into or extract information out of database125.

In one embodiment, computer 120 is able to access database 125 overnetwork 135. Network 135 may be a local area network, a wirelessnetwork, the Internet or another computer network. In one embodiment,database 125 is a component part of computer 120 and network 135 is notrequired for computer 120 to access database 125. Database 125 maycomprise an inventory of product or any other type of information. Forexample, in a retail setting a customer may use a device to communicatewith an associate regarding whether the retail setting has a particularproduct in stock or where the product is located. The associate may usekey terms to query computer 120 regarding whether the product is instock. Computer 120 may convert the associate's voice to text andrecognize the command regarding whether the product is in stock.Computer 120 then queries database 125 and sends a response back to theassociate and/or customer. The response may be sent back using anaudible signal or a signal to be displayed on a screen at the userdevice. Similar examples may be constructed around product locationdatabases, workforce scheduling systems, on-floor zone assignments, timeclock systems, door counter systems, video surveillance systems, dataaggregation systems or other information systems used for operations andreporting. Alternatively, computer 120 may recognize a command based onthe converted text without a user saying key terms.

Computer 120 and any ancillary programs may detect audio characteristicssuch as “too much background noise”, “speaking too loudly”(over-modulation), “speaking too softly” (under-modulation), “speakingto quickly” or “excessive pausing.” The computer may then issue anaudible prompt to the user to correct the situation for improvedrecognition of spoken words. Systematically monitoring the eachindividual user (not device) and scripted prompts allows the computer tobetter learn the user characteristics while at the same time allows theuser to modify behavior and speech to better communicate with thesystem.

Database 125 may be a local inventory or a larger inventory. In oneembodiment, database 125 is not an inventory but comprises differentdata. For example, a user may employ the device to communicate with andcommand computer 120 to perform a keyword search of the Internet using asearch engine such as a website search engine.

In one embodiment, computer 120 is able to measure or collect PrimaryStatistics related to a communication or a plurality of communicationsbetween devices 105, 110 and 130. The Primary Statistics may be datathat is user generated or is simply context information related to thecommunication. For example, the Primary Statistics may include, but notlimited to such directly measurable quantities such as: engaged oravailable time(s), locations, locations traversed including speed anddirection, listen time, talk time, number of listeners, geographiclocation of the speakers and listeners, type of communication (e.g.,broadcast, private conversations, interruptions, group conversations,announcements, interrupting announcements, mandatory response messages),length of the communication session, initiator of communications,receiver of communications, presence information, keywords spoken orlistened to, tone of voice, speech cadence, banter rate, emotion andinflection (as measured by voice stress analysis tools), lengths ofspeech segments, what policies are used for the communications, when andwhere two or more individuals dwell in close proximity to each other orto specific locations, the speed of movement and pausing of thelistening individuals during/after talking or listening, the frequencythat listeners delay hearing a message or drop out from what a speakeris saying, and/or promptness of responses to what was heard, InertialMeasurement Unit (IMU) data, radio signal strength (RSS), signal tonoise ratio (SINR), measurements from accelerometer, and (X,Y,Z)location coordinates.

Engagement or engagement time refers to the ability for associatesindicate to the system that they are engaged and unavailable to receiveor initiate regular communications. Engaged users can be accessedthrough interrupt user capabilities or via other sounds or prompts heardin the ear or indicated on the device. Thus an engaged user is preemptedfrom receiving a regular communication. Location maps refer to a mapthat shows geographic positions of where a user has been located over aperiod of time or for a given instance. Talk time refers to how long thespeech of a communication lasted. Listen time refers to the amount oftime the ear is listening to information, messages or to other speakers.Geographic location of device may refer to where an employee spendstime, assigned location of an employee, percentage of time employeespends in assigned location, percentage of time employee spends incustomer engagement areas, proximity of one employee to other employees.Motion, speed and motion vector refer the way a user moves, changesdirection, stops and dwells across the observation platform environment.Presence information refers to the availability, status, or statusindicator of a user such as how long the communication device associatedwith the user was turned on and available for communications. Presenceinformation may be similar to presence information used track thepresence of a user in Instant Messaging. Keywords may be keywords thatare identified via computer 120 using speech recognition techniques forthe audible portion of the communication. Emotion and approachabilitymay be obtained by measuring stress in the audible speech, measuringpitch or changes in pitch, inflection, cadence and/or loudness and, theduration of the speech in the audible portion. A speech profile may becreated for a given user and then changes in pitch and speed relative tothe profile may be used to make determinations related to tone andemotion. Third party voice stress analysis (VSA) software may gather andgenerate additional context for making determinations quantitatively.Policies may refer to policy 114 of FIG. 1D.

In one embodiment, computer 120 employs one or more of the PrimaryStatistics to generate or create Secondary Statistics. The generation ofSecondary Statistics may also be described as analyzing or synthesizing.The analyses of the primary and Secondary Statistics are able toquantify sociability potential or social skills of the users who areutilizing the observation platform. The Secondary Statistics may begenerated based on an inference rule. The inference rule may be aspecific algorithmic procedure for taking specified data from thePrimary Statistics and outputting a specific secondary statistic. Theprocedure may be to construct a weighted sum of the inputs to produce asingle output number. More complex algorithmic procedures may produceseveral output numbers by multiple weighted combinations, and mayinclude use of thresholds to produce ‘True/False’ a.k.a ‘0/1’ Booleanvalues or other numerical relations from linear or non-linearoperations.

An inference rule may be changed or tuned during the course of using thepresent technology. For example, during a shift in a retail environment,a manager or others may tune an inference rule to change the SecondaryStatistics that are generated. The Secondary Statistics may refer to avariety of skills or behaviors that are quantified based on the PrimaryStatistics. Having more data means that it possible to implementconditional probability that will lead to more accurate predictions withless uncertainty.

For example, it is known that the functioning of the basic neuralsystem, including the human brain, can be modeled by a statisticalnetwork that employs evolved heuristics. The engineering science of‘neural networks’, which is one of many models for the extraction ofmachine intelligence from input data, is inspired by this fact. In thismodel, the inputs to the system are a set of observations, possiblychanging over time, where often the inputs may be ‘unreliable.’ Fromthese “Primary Statistics,” a neural network (or other machine learningincluding Bayesian Networks, generates an abstracted set of metrics. Theabstracted metrics are machine derived: this is to say, the outputs aredriven by the set of inputs. Therefore, these abstracted set of metrics,though being of higher order are also a set of statistics.

The Secondary Statistics are metrics that are derived from the moreprimitive, primary observations, and in the sense that they remainstatistics. So, the terms ‘primary statistic’ and ‘secondary statistic’in no way imply a relation of greater or lesser importance or a feelingof undependability. These terms instead accurately describe the realityof the world and the sense of drawing more sophistication from primarydata, just as primary school is followed by the higher secondaryeducation.

The Secondary Statistics are also used to create an assessment of theuser. For example, the assessment may demonstrate that a user is a go-toperson, a team player, a task-doer, a leader, a teacher, a director,etc. For example, a dimension ofappropriate-customer-oriented-extroversion (‘greeters’) is measured bythe frequency of customer interactions, the length of theseinteractions, motion or dwell time with customers, evidence of apleasant tone and use of appropriate words and keywords. A separatedimension of domain-specific-communication-clarity is measured by thefrequency of staff interactions within appropriate locations and thatcommunications grading modified (on at least a sampled basis) by wordcloud mapping of the words used to an appropriate set. As a thirdexample, the assessment of a manager (“directors”) may have differentcomponents and different weights than those of a greeter, for example.Each of these dimensions are separate from other skills. Additionally,different shifts in different stores may require different mixes ofemployees. The management would not want all greeters, all teachers, orall directors on the floor at the same time. The ability to measure manydata points and to combine these using weights, simple algorithms orsophisticated algorithms into a composite metric is valuable and new.

The Tables below shows examples of types of sociability potentials orskills. The tables demonstrate examples of skill types such as amiable,helper, manager, expert, and loner. Each weight may be represented bynumerical values typically in a range such as 0-5, 0-10, or 0-100:

Skill Type: Amiable Weight Location + balanced mix of dwell time andmotion time where shoppers congregate + high degree of motion withshoppers + moves with deliberation and brisk pace − spends time inbackroom locations and/or break room locations − slow pace and wanderingmotions in isolated locations Contacts + broad range of contact,frequent initiation, frequent concise messages + balanced mix of 1:1conversations, one-to- group conversations, store-wide or chain- wideannouncements + high degree of listener attention (listeners listen inreal time, do not truncate or delay messages) + tendency to respondpromptly in group conversations − contacts to narrow group, longercontact − listeners delay or delete messages without listening to them −group members frequently drop out of conversations − frequentoccurrences of voice stress especially when in group conversations orwhen adjacent to many other associates or other users Adjacencies +frequently and briefly found in same vicinity with many + moves withothers at a brisk pace + tendency to be found adjacent to a wide varietyof other associates − tendency to be found adjacent to only a few of thesame associates.

Skill Type: Helper Weight Location + tendency to be on the floor andfrequently near others for brief periods of time − often found inisolated places or group gathering places Contacts + broad contact,respond more than initiate, longer session + tendency to respond (viavoice or motion) quickly to task messages (e.g., a location task messageor a register backup assistance needed message) + tendency to quicklyrespond verbally to messages containing task-oriented keywords −contacts to narrow group − frequent occurrences of excessive voicestress Adjacencies + often get a call (contact or message), then moveadjacent to another associate − few adjacencies

Skill Type: Manager Weight Location + tendency to be where shopperscongregate + tendency to be “engaged” in high margin areas of thestore + low dwell time at any location+ frequently moves across multipledepartment boundaries + listeners of 1:1 brief messages frequently movewith urgency and clear direction after a conversation − frequentlystationary in office or break room − spends excessive time in lowtraffic areas of the store Contacts + frequent use of ‘Directive orAssignment’ Policies + shows active participation in group conversations(speaks frequently, others respond promptly) + high degree of listenerattention (listeners listen in real time, do not truncate or delaymessages) + brief 1:1 messages to a large number of associates +frequent announcements to whole store + frequent messages left forassociates not yet identified by the system + audible stream containsdirective keywords − long periods of silence − lengthy 1:1 conversationswith a small set of associates − frequent 1:1 conversations to a fewindividuals not in supervisory roles − infrequent announcements −listeners delay or delete messages without listening to themAdjacencies + high degree of motion throughout the store (high aislesper hour metric) that pause briefly near other associates + low dwelltimes with other associates + frequently with other associates whilealso “engaged” (mentoring behavior) − tends to single locations

Skill Type: Expert Weight Location + tends to stay in single ‘expert’location or department (as defined in job) + moves quickly anddeliberately when out of department + moves to all areas in thedepartment + often traverses to a customer service desk or customer helpdesk − other associates do not tend to move toward this person − doesnot participate (low talk and listen times) in group conversations.Contacts + frequent respond to ‘Subject’, ‘Expert’ or ‘Help’ typePolicies + − few associates initiate conversations with this person −most conversations are short − few 1:1 conversations longer than 0:30min − seldom contributes to group conversations Adjacencies + frequentin one or few vicinities with many adjacent associates + frequently withother associates while also “engaged” with shoppers (mentoringbehavior) + other associates tend to move toward this associate to formbrief adjacencies

Skill Type: Loner Weight Location + remains mostly in operationslocations and break rooms + moves slowly in less busy areas of the store+does not tend to move towards where shoppers congregate − tendency todwell near other associates Contacts + seldom initiates conversations +short conversations + few associates are contacted during the shift +low engagement times with shoppers − more contacts of any sort − createsannouncements Adjacencies + few adjacencies with other associates +seldom found near associates indicating they are engaged with a shopper− more adjacencies

In one embodiment, the Secondary Statistics are evaluated againstdesired and undesired observables to validate or discover causal links.For example, enterprise-wide visibility allows comparison of patternsbetween two stores such as store-to-store results and store results atdifferent times or under differing policies or staffing mixes. Use of‘big data’ techniques to identify likely drivers of store gross sales,labor costs, and profitability by tying these external observables tothe various potentially useful dimensions of the assessment. Thesetechniques additionally permit the weighting to be varied to improve thepredictive value of the Secondary Statistics. Weightings may vary byregion, by shift, and by product type. By analyzing a broad data set ofeither historical or real time financial information and thecorresponding workforce scheduling information, the present technologycan determine a target or minimum goal for each shift in order tooptimize a store's financial performance.

The discovered and validated measures can then be used by management toplan, hire, evaluate and guide, and to schedule. Consequent assignmentof parameters to individual employees to: allow predictions of likelybehaviors under various circumstances, prepare better plans (i.e.,staffing mixes through workforce management tools like Kronos), createforecast consequences of hypothetical policy changes, and better train,inspire and measure all staff.

Predictive models can be built using actual historical data to determinesociability score milestones that new hires should attain over a certaintime period. Store management will be systematically notified should newhires fail to meet the configurable milestones. Similarly, associatehistorical sociability score trends can be monitored for substantialdeviations, which could signal a substantial behavior change.

The Secondary Statistics may also show a breakdown of skills or mayclassify skills in different categories. A numerical value may then beemployed to demonstrate the user's or employee's rating or effectivenessfor a given skill. The present technology may operate to generateSecondary Statistics and assessments for a single user or for groups ofusers.

In one embodiment, the Primary Statistics and Secondary Statistics areemployed by computer 120 to generate higher order statistics. Higherorder statistics simply use techniques and algorithms to create anadditional level or layer of quantified sociability score or skills thatare based on the Secondary Statistics.

The Secondary Statistics can be generated in a continuous or dynamicfashion. In other words the Secondary Statistics can be updated over aperiod of time. As new communications are made between employees andother users, more or new Primary Statistics are be gathered and used togenerate new Secondary Statistics and assessments. This may beaccomplished periodically or in real time. Moreover, the type ofSecondary Statistics may change over time.

The Secondary Statistics and assessment may then be made available to amanager, others, or other computer systems. This may be done by themanager or others accessing the information at computer 120 or computer120 may send the information to another computer system or handhelddevice accessible by the manager or others. For example, the informationmay be emailed to the manager or hosted on a website, delivered to adatabase or instantly fed to another computer system.

The Secondary Statistics or higher order statistics may also begenerated based on external statistics that may or may not be combinedwith the Primary Statistics. External statistics come from outside thescope of the observation platform and may refer to: length ofemployment, languages spoken, job identity, employment hours, locationassignments, skills possessed, desired skills, roles, responsibilitiesor social engagement quotient (SEQ) generated by another process.

In one embodiment, a visual representation may be generated based on theassessment. For example, the visual representation may be a map thatshows the geographic location of a user over a period of time within theretail environment. Thus the visual representation may convey where anemployee spends their time while on shift and where the employee islocated when communicating. The visual representation may also depictthe types of communications that are made in certain areas. For example,it may show that an employee with an answer communicates even when inthe break room. Or the visual representation may show that two employeesare likely to only communicate with each other during certain times orin certain places or that two or more employees tend to gather incertain locations.

The Primary Statistics, the Secondary Statistics and the assessment maybe stored at computer 120 or at another location. Computer processesrelated to Primary Statistics, the Secondary Statistics and theassessment may be all performed at one computer such as computer 120 ormay be performing using a plurality of computers via cloud computingtechniques.

With reference now to FIG. 1B, a block diagram of an environment 140 fortraining, monitoring, and mining communications in an observationplatform. Environment 140 includes devices 105, 110 and 130, radio basestation 115, computer 120, transceivers 145, 150, and 155, and regions160, 165, and 170. Environment 140 comprises components that may or maynot be used with different embodiments of the present technology andshould not be construed to limit the present technology. Some or all ofthe components of environment 140 may be described as an observationplatform for structuring a communication.

Transceivers 145, 150, and 155 are capable of sending and receivingsignals to and from radio base station 115 and devices 105, 110 and 130.Transceivers 145, 150, and 155 may or may not be networked to oneanother and to either radio base station 115, computer 120 or both.Transceivers 145, 150, and 155 may be transceivers such as wirelessrouters in a computing network. The transceivers may relay acommunication from a user device to computer 120. A communication orsignal may be routed through a plurality of transceivers before reachingcomputer 120. Transceivers need not connect to any network or computerand may be located throughout the environment as needed for the locationaccuracy desired. Additionally, the transceivers may use a low dutycycle beacon that may be time synchronized with devices in under thecontrol of computer 120.

In one embodiment, the transceivers may be uniquely identifiable suchthat a communication may comprise a characteristic that identifies thecommunication as being routed through a given transceiver. Thisidentification of the transceiver may be employed by computer 120 todetermine a geographic location of a device or user. Thus, acharacteristic of the communication may be an identity of a transceiverand comprises information that is indicative of a geographic position.Computer 120 may determine that a device is in a geographic region thatis associated with a transceiver such as region 160 associated withtransceiver 145. Computer 120 may also use geographic information anduser motion characteristics to predict and pre-set association to thenext likely transceiver.

In one embodiment, computer 120 determines the geographic location of adevice based on a transceiver signal strength received at the devicefrom one or more transceivers. For example, device 130 may receivesignals from both transceivers 150 and 155 each with a correspondingsignal strength. The signal strength data is sent from device 130 tocomputer 120 as a characteristic of a signal or communication sent tocomputer 120. The signal strength data is then used by computer 120 todetermine the geographic position of device 130.

Transceivers 145, 150, and 155 each have an associated region such asregions 160, 165, and 170. The regions may define the transmission rangeof the transceiver or may be defined based on some other criteria. Inone embodiment, the regions may be described as wireless hotspots or802.11 access points (APs). Regions 160, 165 and 170 may be well definedgeographical regions either indoors or outdoors and may be known tocomputer 120. Regions 160, 165 and 170 are depicted as not overlappingone another. However, the regions may or may not overlap one another. Inone embodiment, computer 120 may determine the geographic location of adevice based on its location in one or more regions. For example, device105 may be located in region 160 for its primary communications, yet iscapable of receiving signals strength measurements from regions 165 and170. In another example, regions 160 and 165 may be overlapping andcomputer 120 determines that device 110 is in the overlapping portionsof region 160 and 165 because a characteristic of a communication fromdevice 110 indicates that device 110 is capable of transmitting to andreceiving signals from both transceiver 145 and 150. Thus acharacteristic of signal sent from a user device to computer 120 may becontents of a communication, a portion of a communication correspondingto an audible source, signal strength data of a transceiver or multipletransceivers, an identity of a transceiver or multiple transceivers,geographic position data, or other information.

In one embodiment, computer 120 determines the geographic motion, motionvector, or path of travel of a user based on transceiver signalstrengths received at the device from one or more transceivers. Movementof the communications device 130 may be derived from data regardingsignal strength measurements made from one or more of the transceivers,where the signal strength is measured and sampled at successive timeintervals, via well-known methods. For example, as a user moves aboutthe region in environment 140, the signal strength will increase at onetransceiver device and decrease at another. Movement of thecommunications device 130 may also be derived from internal componentsin the device such as accelerometers, barometers, or magnetic compasses,again via successive time samples of data. This data may be used todetect a more accurate range of movement.

With reference now to FIG. 1C, a block diagram of an environment 180 fortraining, monitoring, and mining communications in an observationplatform. Environment 180 includes devices 105, 110, 111 and 131, radiobase stations 115 and 116, computers 120 and 121, network 135 andregions 175 and 176. Environment 180 comprises components that may ormay not be used with different embodiments of the present technology andshould not be construed to limit the present technology. Some or all ofthe components of environment 180 may be described as an observationplatform for structuring a communication.

In one embodiment, device 105 and 110 are located within region 175. Thecomponents depicted within region 175 may be described as an observationplatform. Region 175 may be described as having a radio range, or spanof operating distance. For example, radio base station 115 may have aphysical limit regarding the distance which it may transmit radiosignals. Therefore, a device outside of the radio range, such as devices131 or 111 will not be able to communicate with computer 120 via a radiosignal transmitted from radio base station 115. Additionally, devices105, 110, 111 and 131 may also have a limited radio range.

These limitations may be overcome by computer 120 relaying thecommunication to either device 131 or a second observation platformwithin region 176 via network 135. Therefore, devices 105 and 110 maycommunicate with either device 111 or 131 where the communications arerelayed by computer 120 and network 135. Region 176 may be described asa second observation platform with components that are duplicates of orsimilar to components of region 175. The regions 175 and 176 maycomprise any number of communication devices or other components suchcomputers, routers, and transceivers. Thus, the present technologyprovides for structured or disciplined communications between at leasttwo user devices, or a plurality of devices, that may or may not bewithin radio range of one another.

In one embodiment, the communications between computer 120 and devices105 and 110 are accomplished via radio signals and the communicationsbetween device 131 and computer 120 are accomplished via network 135. Inone embodiment, the connected between network 135 and device 131 istelephony call such that device 105, which may not be a telephone,places a phone call to device 131, which is a telephone, via theobservation platform. In such an embodiment, network 135 may compriseboth a computer network and a phone network or cloud.

In one embodiment, device 131 and/or region 176 may be physically remoterelative to radio base station 115. For example, all the componentsshown within region 175 may be located within radio range of one anotherat a first location, but device 131 and region 176 are located at asecond and third location outside of region 175. These first, second andthird locations may be separated by any distance. The second or thirdlocation may be hundreds or even thousands of miles away from the firstlocation or may be less than a mile away but still outside of region175. In one embodiment, computer 120 and radio base station 115 arelocated at a first physical address such as a street address for abuilding or other physical location, device 131 is located at a secondphysical address, and computer 121 and radio base station 116 arelocated at a third physical address.

In one embodiment, computer 120 and radio base station 115 areassociated with a retail environment and region 175 includes the retailfloor as well as an office or other area designated for associates,managers, or others relative to the retail environment. However,computer 121 and radio base station 116 are located in region 176 arelocated at a second retail environment. The first and second retailenvironments may be related to one another such as both being afranchise of the same business or enterprise. Thus, a customer orassociate may be located in region 175 associated with a firstfranchise, e.g. a first observation platform, and speak with anassociate using device 111 in a second franchise, e.g., a secondobservation platform. The customer or associate may ask questionsregarding the inventory of an item at the second franchise or speak withan associate at the second franchise that has knowledge not known byassociates at the first franchise.

With reference now to FIG. 1D, a block diagram of an environment 190 formediating a communication in an observation platform. Environment 190includes devices 105 and 110, radio base station 115, computer 120,first communication 104, 106 and 122, metadata 108, attribute 112,policy 114, metadata for devices 118 and play module 124. Environment190 comprises components that may or may not be used with differentembodiments of the present technology and should not be construed tolimit the present technology. Some or all of the components ofenvironment 190 may be described as an observation platform.

In one embodiment, devices 105 and 110, radio base station 115, andcomputer 120 have the same capabilities of their counterparts in FIG.1A. Device 105 is able to send first communication 104 to computersystem 120 via radio base station 115. Computer system 120 may belocated physically proximate to the devices or it may be remote andconnected via a network. Computer 120 may also be a plurality ofcomputers connected using cloud computing techniques. It should beappreciated that first communication 104 may be generated by a useremploying device 105 and the content may include audio, speech, text,images, video, or any combination thereof. First communication 104 mayalso be described as speech, oration, or play. First communication 104may also include additional characteristics such as data indicative of ageographic location of device 105, a timestamp of when firstcommunication 104 was generated and sent, the identity of a userassociated with device 105, etc. In one embodiment, computer 120 storesfirst communication 104 as first communication 106 and parses orgenerates metadata 108 associated with first communication 106 accordingto policy 105. It should be appreciated that metadata 108 may be relatedto the actual content of first communication 104, may be related to theadditional characteristics of first communication 104, or may be acombination. Additionally, metadata 108 may comprise data related to ahistory of the use of device 105 such as statistical data of how manycommunications are sent and received by device 105. Such data may not bepart of first communication 104, but may be stored and accessed inmetadata for devices 118.

In one embodiment, metadata 108 includes content from firstcommunication 104 that directs the destination of the communication. Forexample, first communication 104 may comprise an audible portion withthe words “Bob are you there?” Computer system 120 may convert theaudible portion of first communication 104 to text and parse the phrase“are you there” as a command to relay the communication to “Bob.”Additionally, metadata for device 118 may know that the name “Bob” isassociated with a given device, first communication 104 is then relayedto the given device. Alternatively, computer system 120, may parse thephrase and respond with the known state and location of “Bob,” e.g.,“Bob is available in aisle seven.”

Metadata 108 may also be a unique message identification numbergenerated by computer 120 for first communication 104, a groupidentification number that associates first communication 104 with aseries of related communications, and/or a geographic zone in whichdevice 105 is located in. Metadata 108 may also comprise data associatedwith the status of device 105 and/or the status of the user associatedwith device 105. Such status data may indicate whether the user ofdevice 105 is busy, engaged, available, not on the system, not in rage,in a conversation, in training, etc. The status data may be generated bycomputer 120 and may be based on data from the history of device 105 orfrom first communication 104. Metadata 108 may also be a classificationof a user associated with the device. Such classification may be anexpertise such as a “paint expert” or “cashier” or may be more genericsuch as customer, manager, employee, associate, vendor, etc. Metadata108 may also be a start and stop time of the communication. Metadata 108may also incorporate parts or all of the Secondary Statistics relatingthe social engagement quotient of the individual.

In one embodiment, metadata 108 is parsed into individual attributes 112and stored as a set of attributes. Portions or all of metadata 108 mayalso be copied and stored by computer 120 as metadata for devices 118.In one embodiment, metadata for devices 118 stores metadata for aplurality of devices associated with the observation platform such asdevice 110. It should be appreciated that metadata 108, attributes 112and metadata for devices 118 are each controlled by policy 114. Policy114 comprises policies, instructions, and/or rules for the generation,usage and storage of metadata. For example, policy 114 may dictate thatevery communication, such as first communication 104, should have anattribute stored indicating the geographic location of the device whenit sent the communication. In one embodiment, policy 114 determines thelength of time an attribute is stored for. In one embodiment, policy 114is programmable or customized. In other words, policies may be changedduring the operation of the observation platform and may be assigned todevices, groups of devices or individual users, if known. The devicesmay store a portion of the policy to control what data is sent with acommunication to computer system 120. Changes in the policy may be sentto the devices. However, policy 114 may simply be a default policy. Oneexample of a set of policies is a walkie-talkie emulator policy wherethe policies allow the devices in the observation platform to emulatewalkie-talkies.

Metadata for devices 118 may include metadata and/or attributes similarto those described for metadata 108 only in relation to a plurality ofdevices rather than just one device. In one embodiment, computer system120 compares attributes 112 to the attributes for other devices storedin metadata for devices 118 to identify a recipient device for firstcommunication 104. In one embodiment, the identification is accomplishedby matching one attribute. For example, first communication 106 maycomprise an attribute that matches an attribute stored in metadata fordevices 118 that is associated with device 110. Thus the matchingattribute identifies device 110 as a recipient device for firstcommunication 104. Once such an identification is made, firstcommunication 104 may be relayed to device 110 as first communication122 via computer system 120 and radio base station 115. Firstcommunication 122 may be identical to first communication 104 or maysimilar to first communication 106 and comprise metadata 108.

In one embodiment, computer system 120 identifies a recipient device bymatching a single attribute. In one embodiment, computer system 120 willrelay first communication 104 to every device that has a matchingattribute with any one of the attributes from attributes 112. Forexample, device 110 may have a geographic position attribute thatmatches a first attribute from attributes 112 while a third device has atimestamp attribute related to a second attribute of attributes 112. Inthis example, both device 110 and the third device will be relayed thecommunication as recipient devices. It should also be appreciated that aplurality of devices may all have the same attribute matching a firstattribute from attributes 112 and each of the plurality of the devicesare then relayed the communication.

In one embodiment, computer system 120 will not relay firstcommunication 104 to a device that has a matching attribute if theattribute is blocked by an inhibitor for the given device. Such aninhibitor may be received at computer system 120 from a device or may begenerated and stored by computer system 120. In one embodiment, thegeneration of inhibitors is controlled by policy 114. For example, aninhibitor may be associated with device 105 in relation to firstcommunication 104 such that computer system 120 does not relay firstcommunication 104 back to device 105 even if a matching attribute isfound. Other inhibitors may be related to the status of a device. Forexample, if a device status is “busy” or “engaged with customer” thancomputer system 120 may be inhibited from identifying such a matchingdevice as a recipient device.

In one embodiment, an inhibitor may be overridden by an attribute. Forexample, a communication that is marked “urgent” or “interrupt” mayoverride certain inhibitors or any inhibitor associated with the statusof a device.

In one embodiment, computer system 120 identifies a recipient devicebased on a voting system involving a plurality of matches of attributesand/or inhibitors. For example, in the voting system, an attribute maybe assigned a numerical value such as +1 and an inhibitor a value of −1.The voting system will then tally all of the numerical values and if thetally for a given device is positive, or above a predeterminedthreshold, then the given device will be identified as a recipientdevice and relayed the communication. It should be appreciated that someattributes may also be given a negative value such as status oravailability of a device or the location of a device in a predeterminedzone.

In one embodiment, device 110 receives the relayed first communicationat play module 124. Play module 124 may operate to automatically play arelayed communication once it is received. Play module 124 may alsotrigger a notification to a user of device 110 that a relayedcommunication has been received. In one embodiment, the playback of therelayed communication is governed by a policy on play module 124 that isassociated with policy 114. Computer system 120 may track, record and/ortimestamp all information and other audio streams that are played toeach user.

In one embodiment, device 110 is utilized to generated and send a secondcommunication from device 110 back to computer system 120. Computersystem 120 may then similarly parse metadata for the secondcommunication and determine that it is responsive to first communication104 and relay the second communication to device 105. This determinationmay be made by matching attributes of metadata and may also be based ontimestamps of the communications in conjunction with policy. In oneembodiment, the second communication is relayed to all of the devicesthat the first communication was relayed to.

In one embodiment, the first communication is relayed to a plurality ofrecipient devices which is described as a one-to-many communication.Once a second communication, or responsive communication, is receivedthen subsequent communications may only be sent to and from the firstdevice and the responsive device. Thus a one-to-many communicationstream may be narrowed to a one-to-one communication stream where acommunication stream is defined as a series of communications. Byresponding to a first communication, the user of the responding deviceself-selects herself to be included in the future communication stream.

In one embodiment, the first and second communication are sent andreceived by the devices in substantially real time. For example,computer system 120 may be parsing and matching metadata and relayingthe communications, but computer system 120 may operate on the scale ofmicroseconds such that the users of the devices will not perceive anylag and the series of communications will be perceived to occur in realtime. Thus the present technology may be described as operating anobservation platform whose point is satisfying unique requirements of anenvironment such as a retail environment. The present technology isbuilt around, in at least one method, forwarding voice messages fast byselecting what messages to play on what devices. The selection is madeemploying by comparing metadata or message tags to tags on objectsassociated with each device or communicator. However, communications mayoccur within the observation platform that are peer-to-peer between twoor more users and their devices and are not intercepted and relayed orforwarded by a computer system. In any case, the Primary Statistics maybe gathered and used by the computer system.

In one embodiment, first communication 104 may be generatedautomatically by device 105 in response to a predetermined event, actionor series thereof. For example, an employee's time may be tracked fortime card purposes using communications from the device. Communicationsmay be sent to that log when and where an employee is located and thecommunications may be sent automatically upon the device entering orexiting geographic zones.

With reference now to FIG. 1E, a block diagram of an environment 191 forusing structured communications in an observation platform with cloudcomputing. Environment 191 includes devices 105 and 110, radio basestation 115, computer 120, network 135, device 131, region 175,computers 192, 193, 194, and 195. Environment 191 comprises componentsthat may or may not be used with different embodiments of the presenttechnology and should not be construed to limit the present technology.

In one embodiment, devices 105 and 110, radio base station 115, computer120, network 135, device 131, region 175, have the same capabilities oftheir counterparts in FIG. 1C. Device 105 is able to send firstcommunication 104 to computer system 120 via radio base station 115.Region 175 may depict a radio range of device 105, device 110 and radiobase station 115. Region 175 may also describe a first observationplatform. Computer system 120 is depicted as being connected tocomputers 192, 193, 194, and 195 via network 135. In one embodiment,region 175 is physically remote or not proximate to computers 192, 193,194, and 195 and device 131. For example, region 175 may be a in aretail setting and computers 192, 193, 194, and 195 are located anywhereelse in the world and may be separated by hundreds or thousands of milesor may be located just outside of radio range of radio base station 115.It should be appreciated that computers 192, 193, 194, and 195 may ormay not be located physically proximate to one another.

In one embodiment, computers 192, 193, 194, and 195 may be used forcloud computing techniques. Computer 120 may be in contact with one ormore of the computer such as computer 192 and computer 193 as depictedby the arrows connecting computer 192 and computer 193 to network 135.In one embodiment, computer 120 forwards data and commands to a singlecomputer such as computer 192, computer 192 then forwards data andcommands to other computers. In one embodiment, computers 192, 193, 194,and 195 perform functions for the present technology and then sendresults back to computer 120. For example, cloud computing may be usedto perform steps such as deriving context information from a signal anddetermining a destination based on the context information. One or moreof computers 192, 193, 194, and 195 may send results back to computer120. Thus a portion of the computational burden and storage requirementsare taken from computer 120 and the hardware requirements for anindividual observation platform are reduced.

Computers 192, 193, 194, and 195 may be networked to one another using avariety of techniques and may be connected as nodes in a peer-to-peernetwork. Computers 192, 193, 194, and 195 may be personal computers,server computers, virtual computers, or any number of other computers.It should be appreciated that all of the processes of the presenttechnology may employ cloud computing for some or all of the stepsassociated with the process. Specifically, processes 300, 400, 500, 600,700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, and 1800may all employ cloud computing techniques. Through the use of cloudcomputing, portions of the present technology may be virtualized.

With reference now to FIG. 2, a block diagram of an environment 200 fortraining, monitoring, and mining communications in an environment.Environment 200 includes radio base station 115, computer 120, users205, 210, 215, 220, 225, 230, and 235, structure 240, area 245, area250, radio devices 255 and 260 and user 265. Environment 200 comprisescomponents that may or may not be used with different embodiments of thepresent technology and should not be construed to limit the presenttechnology.

Environment 200 depicts a setting in which the present technology may beemployed. Environment 200 may be, but is not limited to, retailsettings, public-stage floors, schools, restaurants, hospitalityoperations, outdoor venues, concerts, police scenarios, disaster areas,and other environments where communications occur between users. Areas245 and 250 are depicted as being enclosed. However, the presenttechnology may be implemented in an outdoor or indoor environment or acombination of the two. Users 205, 210, 215, 220, 225, 230, and 235 aredepicted as each holding a device such as device 105 of FIG. 1. Thedevices do not necessarily need to be handheld. Users 205, 210, 215,220, 225, 230, and 235 may be a variety of different types of users. Forexample, the users may be associates and customers intermingled in aretail setting. Area 245 may be the retail floor while area 250 is aback office or other area designated for associates, managers, oremployees of the retail environment.

Structure 240 may be a display, shelves, aisle divider, or otherstructure that physically separates spaces in area 245. For example,users 205, 210, and 215 are depicted as being in separate space of area245 than users 220, 225, 230, and 235. Computer 120 may be able tointeract with users 205, 210, 215, 220, 225, 230, and 235 and determinethe user's geographic locations as well as act as a central hub for allcommunications between the users. In one embodiment, computer 120recognizes a group of users associated with communication devices. Thegroup may be based on a classification or type of user or may be basedon a location of said users. In one example, computer 120 recognizesthat users 205, 215, 230, and 235 are associates and users 210, 220, and225 are customers in a retail setting. The associates may be considereda first group and the customers a second group. In a second example,computer 120 recognizes that users 205, 210, and 215 are a first groupin a separate space of area 245 than the second group of users 220, 225,230, and 235. Computer 120 may then employ the recognition of groups togenerate visual representations (instantaneous or time-averaged) offeatures of the group and its communications. It should be appreciatedthat groups can simultaneously exist in many locations and are notconstrained by building walls or geography.

In one embodiment, environment 200 comprises radio devices 255 and 260used for communication with user devices and radio base station 115.Radio devices 255 and 260 may or may not be networked with radio basestation 115 to provide additional coverage or range for radio basestation 115. For example, radio devices 255 and 260 may be antennas orradio repeaters for radio base station 115. In one embodiment, radiodevices 255 and 260 are wireless routers for computer networking.Computer 120 may employ radio devices 255 and 260 to determine ageographic location of a user. Radio devices 255 and 260 andtransceivers 145, 150 and 155 may each have the same capabilities andfeatures as one another.

The geographic location or position of a user may be determined bycomputer 120 receiving periodic clues or evidence of the geographiclocation of the user device and then computer 120 infers or deduces thegeographic location based on the evidence or clues. For example, theuser device associated with user 205 may receive a plurality of signalsfrom radio base station 115 and radio devices 255 and 260. Each signalhas a unique signature at the current position of user 205. Thesignatures of each source are periodically sent to computer 120 or as acomponent characteristic of any communication. Computer 120 may thendetermine the geographic position of user 205 based on the signatures ofthe sources it reports. In one embodiment, the user device knows itsgeographic position based on geographic position component which is partof the user device. The geographic position component may be a componentdevice or chip that employs the global positing system, other satellitenavigation system, inferred signals, radio signals or RFID signals fordetermining a geographic location or position. A user device with ageographic position component may transmit the determined geographicposition to computer 120 periodically or as part of a communication.Thus computer 120 may know the location of a user at a given time basedon the geographic position of the device associated with the user.

In one embodiment, user 265 interfaces with computer 120 to use thepresent technology to optimize communications. Computer 120 maydetermine and display performance metrics or visual representationsregarding communications to user 265. User 265 may then use theperformance metrics and visual representations to make decisions. Forexample, user 265 may be a manager of associates who can identify that acustomer has asked for assistance at a given location but no associateshave responded. The manager may then use the present technology torequest an associated to assist the customer. In one embodiment, user265 is able to directly use computer 120 and radio base station 115 tocommunicate with other users by individual identification, location orproximity groupings, role groupings or contextual groupings.

In one embodiment, user 265 interfaces with computer 120 to use thepresent technology to optimize geographic location. User 265 may be acustomer and requests help from computer 120. Computer 120 determinesthe associate or user nearest the location of user 265 and provides thecurrent and updated location of user 265 until intercepted by theassociate or user. In one embodiment, user 265 may request helpverbally, not engaging computer 120, and that request is heard by allnearby associates whose context is “not engaged with shoppers” or asotherwise determined by the policy.

In one embodiment, computer 120 derives performance metrics, businessmetric or metric from the communications between users. The metrics maybe used to generate visual representations. The metrics and/or visualrepresentations may be employed to make decisions. The metrics andvisual representations may be sent to another computer system or device.A metric may be based on the behavior of a user, the spoken words of theuser, the context of the user, the location and movement of the user,information carried by the tone and quality of voice, the user'ssignaled communications, or the primary or Secondary Statisticsassociated with the social engagement quotient.

A sales performance metric may be determined by linking sales withusers, measuring busy (or “engaged with shopper”) times of users, andascertaining busy status of user. The busy status of a user may indicatethat the user is engaged in a communication, a task, assisting acustomer, listening to information or otherwise occupied. A responsetime metric may also be determined by measuring the time it takes toanswer a user's question, how long it takes to receive assistance afterasking for it, or how long it takes to arrive at a requested location. Acustomer satisfaction metric may also be derived based on storage andplaying or conversion of speech-to-text of the associate's andcustomer's communication. A task performance metric may be determined bymeasuring the length of time an associate is currently engaged inperforming said task, including noting pending and completed tasks.Metrics may be used by a manager or others to reward good behavior orcorrect undesired behavior. Additionally, because the communications andother audio information have been recorded, the communications may beused in training as examples.

Visual representations may be described as communication trafficintensity maps between users and/or groups such as who talks to whom,how frequently and at what time of day; who asks questions and whoresponds; who responds to tasks, when and how long it took to respond;and listening behavior for training podcasts, messages, announcements,conversations including such information as where they listened, whenthey listened and how they moved during and after the listening. Visualrepresentations may also be described as location maps such as, a statusof when users indicate that they are engaged, busy or available, whenusers ask questions; quiet areas where no communications or engagementsare occurring; where users are not located; where selling tips were leftand by whom; location-based-tasks and the times it takes to completethem; a path of where users have traveled geographically; and a map ofthe environment. With this observation platform for structuringcommunications, a more complete observation of many of the events in theinteraction between and among all users can be observed, cataloged, andanalyzed, providing a great deal of useful information to any manager,others, or relevant computer system.

Operations of Using Structured Communications in an Observation Platform

FIG. 3 is a flowchart illustrating process 300 for using structuredcommunication in an observation platform in accordance with oneembodiment of the present technology. Process 300 may also be describedas disciplining communications in an observation platform. In oneembodiment, process 300 is a computer implemented method that is carriedout by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 300 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 302, a signal from a first communication device is received at asecond communication device associated with a computer system, wherein afirst characteristic of the signal may correspond to an audible sourceand a second characteristic of the signal may correspond to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may be the voice of a user, the signal characteristics mayinclude signal signature information and contextual/environmentalinformation may include user status (e.g., engaged or on-break) and/orbackground noise levels. It should be appreciated that the signal mayactually be a plurality of signals. For example, a first signal may be atransmission of the first characteristic corresponding to the audiblesource and the second signal may be the second characteristiccorresponding to the information indicative of geographic position ofthe first communication device.

At 304, a first user associated with the first communication device isrecognized at the computer system.

At 306, context information for the signal is derived at the computersystem associated with the second communication device. The contextinformation may be geographic information, data regarding length or timeof communication, or text of the communication. In one embodiment,speech to text recognition techniques are employed to convert an audiblecommunication to text. In one embodiment, the context information is acommand for the computer system to perform. In one embodiment, thesignal is encrypted or encoded uniquely with respect to the firstcommunication device. The context information may be a command to thecomputer system. For example the computer system may be commanded toaccess a database in response to a query or may be given information tostore for future reference.

In one embodiment, the information is a command and the command may beissued verbally by a user in a communication. For example, a user mayspeak into a communication device the phrase “hello everybody” thus thecommunication is the spoken phrase and the computer system may derivethat the communication is to be sent to everybody. The computer systemthen relays the signal to everybody associated with the communicationobservation platform. In another example, the communication may be thephrase “hello Bob.” The computer system derives that the destination ofthe communication is Bob; the communication is then relayed only to Bob.

The Table below shows examples of Communication Phrases and DerivedContext information. Specific examples using sample vocabulary are givenas well as more general cases indicated by the brackets [ ].

Communication Phrase Derived Context Information “Hello Everybody” Thecommunication is to be relayed to a Hello [Group] group defined as“everybody” and anyone may respond. Context information such as“engaged” may limit those who hear and may respond to the “Hello”phrase. “Hello Bob” The communication is to be relayed to an Hello[Person] individual identified as “Bob” and only “Bob” hears the messageand is able to respond. Context information such as “engaged” may resultin the computer providing additional information to the caller such asthe state of the user (e.g., “engaged”) and other factors such aslocation. “Hello Workshop” The communication is to be relayed to Hello[Location] everyone associated with the “Workshop” location. Contextinformation such as “engaged” may limit those who hear and may respondto the “Hello” phrase. “Hello Process Experts” The communication isrelayed to all identified Hello [Group] as the group, “Process Experts.”These people or machines may be physically located in any region orenvironment. Context information such as “engaged” may limit those whohear and may respond to the “Hello” phrase. “Urgent Bob” or Thecommunication is an urgent “Interrupt Bob” communication to be relayedto “Bob.” Such Interrupt [Person] a command may interrupt “Bob” if he isInterrupt [Group] “engaged” or communicating with others or Interrupt[Location] the system as defined by the operator of the environment.Once interrupted, communication is between the caller and original user(i.e., Bob) and may or may not include others who may have been talkingwith Bob at the time. “Message Bob” Leaves a message that persists for apre- Message [Person] determined interval. Messages for groups Message[Group] are heard as persons become available. Message [Location]Messages for locations are heard as persons become available or enterthe location area. Special cases for ‘messages” include delivering audioinformation to groups such as Marketing Departments, Buyers, Help Desks,Websites, Technical Support or Product improvement requests.“Announcement The communication is to be relayed to Everybody”“everyone” as a bulletin. Those users who Announcement [Group] areengaged or not yet on the system will hear the bulletin when they becomeavailable. “Selling tip for the side The communication is to be relayedto those hallway” who are within or enter the side hallway asAnnouncement an announcement. No response is [Location] anticipated.“Absolute The communication is delivered to all who Announcement for areavailable and in the proper context. A Maintenance Team” response ismandatory. The system records Absolute Announcement the time, location,user and spoken response [Group] or [Location] or for later analysis orstorage. [Person] “Where is Steve” The communication is a command toWhere is [Person] determine a geographic location of Steve Where is[Group] and to send a message back to the communication device from thecomputer system that speaks the response. The response may also includecontextual information such as “Steve is available” or Steve is engaged”or other information from other sources such as “Steve is on break.”Steve does not need to hear that his status was being probed, althoughit is possible to alert him. “Who is near the central The communicationis a command to hallway” determine who is geographically located nearWho is near [Location] the central hallway region and to send a messageback to the communication device from the computer system that speaksthe response. The response may include additional contextual informationfor the persons in that location. “Go to simple menu” The communicationis a command for the Command [profile] computer system to go to thesimple menu profile and to send a message back that speaks the phrase“you will now go to simple menu.” This feature allows individual usersto move into different command, control and skill level profiles withinthe system. “Does anyone know if Some formats of commands are natural towe have . . . ?” the users, but not is a structured speech Spoken Stringpattern. In this case, the words, “Does anyone know . . . ” may triggerthe computer to send this message to group of people who know wherethings are. Additional contextual information may limit that group to adepartment or location. Lost sale report Initiates a set of questions todetermine the reason for a lost sale. Typical categories are:stock-outs, selection limits (e.g., could have sold one in blue), orcompetitive win (e.g., they have this for 20% less on Amazon). ActivityReport Queries the door counter system for shopper arrival and densityinformation. Goal Report Provides information from POS systems regardingthe financial performance of the sales associates and store POSinformation. Message to Tech Connects the communication device toSupport technical support that may be located physically remote from theobservation platform.

The phrase “Go to simple menu” may be a command to enter a differentmenu structure for such activities as new-user learning, learning aboutproducts or business, listening to communications, or set-up functionssuch as group participation and default settings for the individual.

At 308, a geographic location of the first communication device isdetermined based on the second characteristic of the signal and at leastone other source of information. For example, the at least one othersource of information may be a router that the signal is routed through,a signal strength of the signal, information from the secondcommunication device, etc.

At 310, a copy of at least one characteristic of the signal is stored ina storage medium and is made available for performance metric analysis.In one embodiment, the performance metrics are key performance metrics.At least one characteristic may be, but is not limited to, a time stamp,engaged, available status, a message, a voice file, a location, a signalsignature, a type of message, text corresponding to a message, commandsused to initiate the message, other contextual information about theuser and an identity of the path the signal was routed through.

At 312, instructions are received at the computer system comprising thepolicies or rules for the relaying the signal to the destination derivedfrom the context information. The policies may instruct to whom and tohow the communication is to be relayed. For example, information derivedfrom a communication may command that the communication be sent toeveryone associated with the geographic location of “Workshop.” However,the policies may instruct that the communication is only relayed tothose associated with the “Workshop” who are designated as available ornot busy. The policies may also comprise a predetermined time or alifetime in which a response may be relayed to an availablecommunication device.

At 314, the signal is relayed to a destination derived from the contextinformation. The destination may be another user or a plurality of useror the computer system itself. The destination may be located outside ofa radio range associated with the second communication device or beotherwise physically remote relative to the second communication device.

At 316, a data entry and visual representation is generated indicatingthe geographic position of the first communication device with respectto a geographic environment in which the first communication device islocated. For example, the visual representation may be a map depictingthe location of users or where users have been. The data entry andvisual representation may include a status indicator of the user such aswhether the user is busy or available.

FIG. 4 is a flowchart illustrating process 400 for using a structuredcommunication in an observation platform in accordance with oneembodiment of the present technology. In one embodiment, process 400 isa computer implemented method that is carried out by processors andelectrical components under the control of computer usable and computerexecutable instructions. The computer usable and computer executableinstructions reside, for example, in data storage features such ascomputer usable volatile and non-volatile memory. However, the computerusable and computer executable instructions may reside in any type ofcomputer usable storage medium. In one embodiment, process 400 isperformed by the components of FIG. 1A, 1B, 1C or 2. In one embodiment,the methods may reside in a computer usable storage medium havinginstructions embodied therein that when executed cause a computer systemto perform the method.

At 402, a signal from a first communication device is received at asecond communication device, wherein a first characteristic of thesignal corresponds to a voice of a first user and a secondcharacteristic of the signal corresponds to information indicative of ageographic position of the first communication device. Additionalcharacteristics of the signal may include contextual information andenvironmental information. For example, the audible source may be thevoice of a user, the signal characteristics may include signal signatureinformation and contextual/environmental information may include userstatus (e.g., engaged or on-break) and/or background noise levels. Itshould be appreciated that the signal may actually be a plurality ofsignals. For example, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

At 404, the first user associated with the first communication device isrecognized.

At 406, text or machine code related to the voice of the first user isrecognized.

At 408, context information from the text or machine code is derived ata computer system associated with the second communication device,wherein the context information corresponds to a command related to thetext or machine code.

At 410, the text or machine code is stored in a storage medium fordeveloping performance metrics.

At 412, the signal is relayed to a destination derived from the contextinformation. The destination may be located outside of a radio rangeassociated with the second communication device or be otherwisephysically remote relative to the second communication device.

FIG. 5 is a flowchart illustrating process 500 for observing andrecording users of communication devices in accordance with oneembodiment of the present technology. In one embodiment, process 500 isa computer implemented method that is carried out by processors andelectrical components under the control of computer usable and computerexecutable instructions. The computer usable and computer executableinstructions reside, for example, in data storage features such ascomputer usable volatile and non-volatile memory. However, the computerusable and computer executable instructions may reside in any type ofcomputer usable storage medium. In one embodiment, process 500 isperformed by the components of FIG. 1A, 1B, 1C or 2. In one embodiment,the methods may reside in a computer usable storage medium havinginstructions embodied therein that when executed cause a computer systemto perform the method.

In one embodiment, process 500 is a management observation tool forkeeping track of mobile human resources and collecting data on theiractivities.

At 502, a first user associated with a first communication device and asecond user associated with a second communication device are recognizedat a central computer system.

At 504, geographic locations of the first communication device and thesecond communication device are tracked at the central computer system.In one embodiment, tracking means storing data about location and anyspoken information.

At 506, a communication between the first communication device and thesecond communication device are tracked and recorded at the centralcomputer system, wherein at least a portion of the communication is anaudible communication.

At 508, features of the communication are identified at the centralcomputer system. Features may be described as characteristics or dataregarding the communication itself. The features may be user status suchas engaged/available, location of a user, communication history of theuser, context of the communication, keywords used in the communication,a classification of the communication, time stamps or portions of theprimary or Secondary Statistics associated with the social engagementquotient.

At 510, the features are made available to a manager, operations staffor operations machines for making decisions or informing the users thatnew actions are requested.

FIG. 6 is a flowchart illustrating process 600 for characterizingcommunications in a group of users in accordance with one embodiment ofthe present technology. In one embodiment, process 600 is a computerimplemented method that is carried out by processors and electricalcomponents under the control of computer usable and computer executableinstructions. The computer usable and computer executable instructionsreside, for example, in data storage features such as computer usablevolatile and non-volatile memory. However, the computer usable andcomputer executable instructions may reside in any type of computerusable storage medium. In one embodiment, process 600 is performed bythe components of FIG. 1A, 1B, 1C or 2. In one embodiment, the methodsmay reside in a computer usable storage medium having instructionsembodied therein that when executed cause a computer system to performthe method.

At 602, a group of users is recognized, at a computer system, whereineach user of the group of users are associated with communicationdevices. The group of users may be recognized based on a classificationof the user or a geographic location of the users. For example, aclassification of the users may be whether the user is an associate or acustomer in a retail setting.

At 604, a communication between the communication devices is recorded atthe computer system, wherein at least a portion of the communication isan audible communication. In one embodiment, at least a portion of thecommunication is a pre-recorded audible communication.

At 606, geographic locations of the communication devices are recordedat the computer system. The location may be determined based on signalsignatures or other “clues” from other devices sent periodically or withthe communication indicative of the location.

At 608, features are identified based upon the communication. Featuresmay be described as characteristic or data regarding the communicationitself. The features may be a user status such as engaged/available,location of a user, communication history of the user, context of thecommunication, a classification of the communication, a frequency ofcommunications between two users, a length of a communication, keywordsused in the communication, a response time to a communication, timestamps or the primary or Secondary Statistics associated with the socialengagement quotient.

At 610, a visual representation of the features is generated at thecomputer system. The visual representation may depict when a user ofsaid group of users is engaged in said communication, when a user ofsaid group of users asks a question in said communication, who respondsto the question, where each user of said group of users are located, andwhere said group of users are not located. Alerts, either visual orverbal, may be generated depending on the rules and policies establishedby the system operators.

At 612, the visual representation is made available to a manager,operations staff or operations machines for making decisions orinforming the users that new actions are requested.

FIG. 7 is a flowchart illustrating process 700 for using structuredcommunication in a plurality of observation platforms in accordance withone embodiment of the present technology. Process 700 may also bedescribed as disciplining communications in an observation platform. Inone embodiment, process 700 is a computer implemented method that iscarried out by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 700 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 702, a signal in a first observation platform is received from afirst communication device at a second communication device associatedwith a computer system wherein a first characteristic of the signalcorresponds to an audible source and a second characteristic of thesignal corresponds to information indicative of a geographic position ofthe first communication device, and wherein the second observationplatform is associated with a radio range. Additional characteristics ofthe signal may include contextual information and environmentalinformation. For example, the audible source may be the voice of a user,the signal characteristics may include signal signature information andcontextual/environmental information may include user status (e.g.,engaged or on-break) and/or background noise levels. It should beappreciated that the signal may actually be a plurality of signals. Forexample, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

At 704, a first user associated with the first communication device isrecognized at the computer system.

At 706, context information for the signal is derived at the computersystem associated with the second communication device. The contextinformation may be geographic information, data regarding length or timeof communication, or text of the communication. In one embodiment,speech to text recognition techniques are employed to covert an audiblecommunication to text. In one embodiment, the context information is acommand for the computer system to perform. In one embodiment, thesignal is encrypted or encoded uniquely with respect to the firstcommunication device. The context information may be a command to thecomputer system. For example the computer system may be commanded toaccess a database in response to a query.

At 708, the signal is relayed from the computer system to a secondcomputer system associated with a second observation platform via acomputer network

At 710, the signal is relayed to a destination in the second observationplatform via the second computer system derived from said contextinformation.

FIG. 8 is a flowchart illustrating process 800 for performing structuredcommunications in an observation platform in accordance with oneembodiment of the present technology. Process 800 may also be describedas disciplining communications in an observation platform. In oneembodiment, process 800 is a computer implemented method that is carriedout by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 800 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 802, a signal is received from a first communication device at asecond communication device associated with a computer system, whereinthe computer system is associated with an organization, wherein a firstcharacteristic of the signal corresponds to an audible source and asecond characteristic of the signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may be the voice of a user, the signal characteristics mayinclude signal signature information and contextual or environmentalinformation may include user status (e.g., engaged or on-break) and/orbackground noise levels. The organization may be a retail environment,hospitality venue, a school, an event, a military organization, a prisonorganization, customer service, manufacturing organization, a factory, adisaster response team, or any environment where humans interact withone another to accomplish a purpose. The first communication device maybe a handheld device that is capable of sending and receiving signalsand may comprise a display, a microphone and a speaker. The firstcommunication device may be owned by the organization and issued to theuser or may be the user's personal property such as a smart phoneexecuting an application. The second communication device may be a radiobase station as described herein. It should be appreciated that thesignal may actually be a plurality of signals. For example, a firstsignal may be a transmission of the first characteristic correspondingto the audible source and the second signal may be the secondcharacteristic corresponding to the information indicative of geographicposition of the first communication device.

At 804, a user is identified as associated with the first communicationdevice at the computer system. In one embodiment, 804 only identifiesthat there is a user employing the communication device. The actualidentity of the user may remain anonymous to the computer system or theuser may be identified. The user may be identified using one or acombination of several different techniques. The user may be identifiedvia a unique signature of the communication device associated with theuser. For example, the user's communication device may be a smart phonerunning an application. The smart phone may be the user's personalproperty and is always associated with the user. In one embodiment, theuser may be identified upon activation of the communication device orthe application. For example, a user may enter an environment, activatea communication device and then give user credentials that identify theuser. This may accomplished via voice commands or text inputs. In oneembodiment, the user credentials are associated with a user profile, butthe actual identity of the user remains anonymous. In one embodiment,the user may activate a communication device and self-identify.Identifying a user may be automatic taking place without the user'sknowledge, or may require the user to acknowledge or give permission forthe computer system to identify the user.

At 806, the audible source of the signal is converted to text or machineunderstandable language at the computer system. This may occur usingspeech-to-text techniques or other speech recognition techniquesemployed by computer systems.

At 808, a query related to the organization is derived based on the textor understanding at the computer system. The query may be any number ofqueries from the user. The user may ask for general assistance or mayask a more specific question such as whether an item is in stock, wherean item is located, what sales are taking place, technical details orfeatures regarding an item.

At 810, a response to the query is compiled at the computer system,wherein the response represents the organization. For example, theresponse relates to the purpose of the organization. In one embodiment,the response is regarding a location or status of a person or an itemwithin the organization. The computer system may access a database tocomplete the response. The database may be a local database such as aninventory of a local store, or may access a database in part of a largernetwork associated with the organization, or may access a databaseassociated with the Internet. In one embodiment, the computer systemperforms a keyword search of the Internet using a search engine tocomplete the response.

At 812, the response is sent to the first communication device, whereinthe response is audible at the first communication device. In oneembodiment, the response is initially a text response that is convertedfrom text to speech. The conversion may occur at the computer systemsuch that a signal with an audible portion is sent to the firstcommunication device, or a text message may be sent to the firstcommunication device where it is converted to speech. The response maybe recorded by the organization in a computer system and may also besent to a person associated with the organization such as a manager,supervisor or others. Thus, a person associated with the business maymonitor the responses of the computer system and may be aware of theneeds or requirements of the user associated with the firstcommunication device.

At 814, a prior user history of the user is associated with the firstcommunication device. The user history may be a user profile that may ormay not identify the user. The history may have a list of all thetransactions of this user associated with the organization. The historymay also comprise information provided by the user such as likes anddislikes or preferences regarding which person the user wishes to beserved by while in the organization.

At 816, the signal and the response are relayed to a third communicationdevice associated with a person representing the organization. Theperson associated with the organization may be a consultant, anemployee, a supplier, a vendor, a sales associate, a civil servant, avolunteer, a manager, or other users. The third communication device maybe a handheld device and may or may not be the same type of device asthe first communication device.

At 818, a second response is received at the second communication devicefrom the third communication device. For example, the personrepresenting the organization may respond using a signal that may havean audible voice portion a text portion or both.

At 820, the second response is relayed to the first communicationdevice. The computer system may initiate a virtual voice connectionbetween the first communication device and the second communicationdevice.

FIG. 9 is a flowchart illustrating process 900 for performing structuredcommunications in an observation platform in accordance with oneembodiment of the present technology. Process 900 may also be describedas disciplining communications in an observation platform. In oneembodiment, process 900 is a computer implemented method that is carriedout by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 900 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 902, a signal is received from a first communication device at asecond communication device associated with a computer system, whereinthe computer system is associated with an organization, wherein a firstcharacteristic of the signal corresponds to an audible source and asecond characteristic of the signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may the voice of a user, the signal characteristics may includesignal signature information and contextual or environmental informationmay include user status (e.g., engaged or on-break) and/or backgroundnoise levels. The organization may be a retail environment, a school, anevent, a military organization, a prison organization, customer service,manufacturing organization, a factory, a disaster response team, or anyenvironment where humans interact with one another to accomplish apurpose. The first communication device may be a handheld device that iscapable of sending and receiving signals and may comprise a display, amicrophone and a speaker. The first communication device may be owned bythe organization and issued to the user or may be the user's personalproperty such as a smart phone executing an application. The secondcommunication device may be a radio base station as described herein. Itshould be appreciated that the signal may actually be a plurality ofsignals. For example, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

At 904, a user is identified as associated with the first communicationdevice at the computer system. The actual identity of the user mayremain anonymous to the computer system or the user may be identified.The user may be identified using one or a combination of severaldifferent techniques.

At 906, a query is derived from the signal of the first device relatedto the organization, at the computer system. The query may be any numberof queries from the user. The user may ask for general assistance or mayask a more specific question such as whether an item is in stock, wherean item is located, what sales are taking place, technical details orfeatures regarding an item or requesting general assistance.

At 908, a person representing the organization is determined to respondto the query, wherein the determining is based on a factor related tothe person representing the organization. The factor may also bedescribed as a characteristic. The factor may be related to the queryfrom the user. For example, the user may ask a question regarding anitem in a given department. The determining may be based on who isassociated with the given department. The factor may also be based onthe status of the person, the availability of the person, the proximityof the person to the user, geographic location of the person, knowledgelevel of the person, authority level of the person, ability of theperson, the social engagement quotient of the person, or a combinationof factors. The determining may determine that a plurality of personsqualify to respond. The signal may then be forwarded to one of theplurality, a subset of the plurality, or all of the plurality ofpersons.

At 910, the signal is forwarded to a third communication deviceassociated with the person representing the organization.

At 912, a determination that no response has been received at the secondcommunication device from the third communication device is made. 912may occur after 910 in an embodiment where 916 and 918 do not occur.However, 912, 914, 916 and 918 may all occur in one embodiment. Suchdetermination may occur after a pre-determined time period has passedwith no response from the third communication device. Such adetermination may or may not preclude the third communications devicefrom later responding.

At 914, the signal is forwarded to a fourth communication deviceassociated with the person representing the organization. 912 and 914may be repeated forwarding the signal to additional communicationdevices until it is determined that a person representing theorganization has responded via a communication device. Alternatively,910 and 914 may forward the signal to a plurality of communicationdevices associated with a plurality of persons representing theorganization. Once any one of the plurality of persons responds, theperson and the user may be placed into a communications channel viatheir communications devices. The communications channel may be privatein the sense that the other members of the plurality of personsrepresenting the organization do not hear subsequent communications overthe communications channel. This may be accomplished via the computersystem associated with the second communications device. The subsequentcommunications may all be relayed or forwarded between the user and theperson representing the organization via the second communication deviceand the associated computer system. In one embodiment, the communicationchannel is open to all members of the plurality of persons representingthe organization. In one embodiment, the communication channel is opento a subset group of the plurality of persons representing theorganization. For example, the subset group may be only persons who aredetermined by the computer system to have knowledge regarding the querymade by the user or may only be persons who are determined to beavailable, or persons who have interest in learning more about thesubject, or some combination of these characteristics.

By forwarding the signal to a fourth communication device or a pluralityof other devices, the circle or group of those required or enlisted tohelp the user is enlarged. In other words, the user may send acommunication or query indicating that the user is in need ofassistance. The computer system determines that a first person or smallgroup of people are requested to assist the user, but if the firstperson or group does not respond, the computer system then determines asecond person or a plurality of persons to assist the user. Thus thegroup of those responding to the assistance request increases. In oneembodiment, the initial communication from the first user may go to adesignated plurality and the first person to respond becomes establishedin a private one-on-one conversation with the first (originating) user.

At 916, a response is received from the third communication device atthe computer system. 916 may occur after 910 in an embodiment where 912and 914 do not occur.

At 918, the response is forwarded to the first communication device. 918may occur after 916 in an embodiment where 912 and 914 do not occur.Process 900 may initiate a virtual voice connection between twocommunication devices where the communication is relayed or forwardedvia the computer system and the second communication device. Thus thecomputer system and the second communication device may be described asmediating the communications.

FIG. 10 is a flowchart illustrating process 1000 for performingstructured communications in an observation platform in accordance withone embodiment of the present technology. Process 1000 may also bedescribed as disciplining communications in an observation platform. Inone embodiment, process 1000 is a computer implemented method that iscarried out by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 1000 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 1002, a signal is received from a first communication device at asecond communication device associated with a computer system, whereinthe computer system is associated with an organization, wherein a firstcharacteristic of the signal corresponds to an audible source and asecond characteristic of the signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may the voice of a user, the signal characteristics may includesignal signature information and contextual or environmental informationmay include user status (e.g., engaged, available or on-break) and/orbackground noise or sub-audible signal levels. The organization may be aretail environment, a school, an event, a hospitality organization, amilitary organization, a prison organization, customer service,manufacturing organization, a factory, a disaster response team, or anyenvironment where humans interact with one another to accomplish apurpose. The first communication device may be a handheld or fixeddevice that is capable of sending and receiving signals and may comprisea display, a microphone and a speaker. The first communication devicemay be owned by the organization and issued to the user or may be theuser's personal property such as a smart phone executing an application.The second communication device may be a radio base station as describedherein. It should be appreciated that the signal may actually be aplurality of signals. For example, a first signal may be a transmissionof the first characteristic corresponding to the audible source and thesecond signal may be the second characteristic corresponding to theinformation indicative of geographic position of the first communicationdevice.

At 1004, a user is identified as associated with the first communicationdevice at the computer system. The actual identity of the user mayremain anonymous to the computer system or the user may be identified.The user may be identified using one or a combination of severaldifferent techniques.

At 1006, a query is derived from the signal related to the organization,at the computer system. The query may be any number of queries from theuser. The user may ask for general assistance or may ask a more specificquestion such as whether an item is in stock, where an item is located,what sales are taking place, technical details or features regarding anitem.

At 1008, a plurality of persons representing the organization aredetermined to respond to the query, wherein the determining is based ona factor related to the plurality of persons representing theorganization.

At 1010, the signal is forwarded to a plurality of communication devicesassociated with the plurality of persons representing the organization.Such a series of communications may be described as a one-to-manycommunication. The “many” group may be default or predefined group suchas all those associated with a given department or all those who areassociated with a given area of expertise. Groups may also be createdbased on criteria such as names, locations, roles, skills, talents,interests, social engagement quotient and/or either engagement oravailability or status.

At 1012, a response is received from a communication device associatedwith one of the plurality of persons representing the organization atthe second communication device.

At 1014, the response is forwarded from the second communication deviceto the first communication device. Thus the communication may go from aone-to-many to a one-to-one communication.

At 1016, a communication channel is opened between the firstcommunication device and the communication device associated with one ofthe plurality of persons. In other words, the communication from thefirst (originating) user is sent to multiple persons. The first personto respond enters into a communication channel between the firstcommunication device and the communication device associated the person.Others who respond within a pre-determined timeframe are also includedin the “channel.” The communication channel may be mediated by thecomputer system and once all users have entered, may not be overheard bythe other persons from the plurality of persons. The usefulness of thisstructure is that it allows ad-hoc group construction by simplyannouncing the intent of the group, and only those responding are tiedinto the private group “channel”.

In one embodiment, the communication may go from a one-to-many to aone-to-few communication. The persons in the few of the one-to-fewcommunication may be a subset of the many persons from the one-to-many.For example, the initial communication may be sent to all those personsholding communication devices. The computer system may then open acommunication channel between the first person to respond where thechannel is also opened to others person representing the store who areassociated with a specific role or department. Thus only one person maybe actively communicating with the user, but other persons may hear thecommunications and may join at any time. Thus the communication may notdisrupt those who are otherwise not interested.

FIG. 11 is a flowchart illustrating process 1100 for sendingnotifications in an observation platform in accordance with oneembodiment of the present technology. Process 1100 may also be describedas disciplining communications in an observation platform. In oneembodiment, process 1100 is a computer implemented method that iscarried out by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 1100 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 1102, a signal is received from a first communication device at asecond communication device associated with a computer system, whereinthe computer system is associated with an organization, wherein a firstcharacteristic of the signal corresponds to information indicative of ageographic position of the first communication device. The organizationmay be a retail environment, a school, an event, a hospitalityorganization, a military organization, a prison organization, customerservice, manufacturing organization, a factory, a disaster responseteam, or any environment where humans interact with one another toaccomplish a purpose. The first communication device may be a handhelddevice that is capable of sending and receiving signals and may comprisea display, a microphone and a speaker. The first communication devicemay be owned by the organization and issued to the user or may be theuser's personal property such as a smart phone executing an application.The second communication device may be a radio base station as describedherein. It should be appreciated that the signal may actually be aplurality of signals. For example, a first signal may be a transmissionof the first characteristic corresponding to the audible source and thesecond signal may be a second characteristic corresponding to theinformation indicative of geographic position of the first communicationdevice.

At 1104, a user is optionally identified as associated with the firstcommunication device at the computer system. The actual identity of theuser may remain anonymous to the computer system or the user may beidentified. The user may be identified using one or a combination ofseveral different techniques.

At 1106, a history of activities of the user associated with theobservation platform is accessed. The history of activities may be auser history, device history or user profile that may or may notidentify the user. The history may have a list of all the priorcontextual information of this user. The history may also compriseinformation provided by the user such as likes and dislikes orpreferences regarding which system characteristics or behaviors the userwants to experience while using the device. In one example, a useracting as a shopper, may describe her likes, dislikes, preferencesand/or interests. In this case, the computer combines the contextualinformation such as location and motion, with spoken information andother related data to match the user preferences with another user onthe system, such as a sales associate. The computer may attempt to findthe preferential associate(s) and notify them that the shopper is in thestore, possibly including other helpful information such as: where theshopper is located, how are they moving (motion vector), what is theirname if they have identified themselves, what they are saying, what theyare listening to, prior pattern of motion and dwell locations and/or anyother relevant contextual data or social engagement quotientinformation. In addition, he associates contacted may hear priorconversations with that shopper to refresh their memory and aid inmaking the shopper experience seamless or may be updated on prior Pointof Sale (POS) information from a separate computer system.

At 1108, a geographic location and possibly a motion vector of the firstcommunication device in the organization is derived at the computersystem. For example, the computer system may determine that the user ison a given aisle such as the cereal aisle in a grocery store or in azone that may correlate to a department such as the lumber department ina hardware store.

At 1110, a notification is sent to the first communication devicewherein the notification is based on the history of activity and thegeographic location and/or motion of the first communication device. Forexample, the notification may alert the user of a coupon or special on agiven item in the organization that is for sale. The coupon or specialmay be for an item that the user previously purchased which knowledgewas obtained by the computer system based on the history of useractivity or stored in a separate computer system. The notification maybe any number of notifications including a text message or an audiblemessage and the notification may be accompanied by an alert such as avibration, LED indication, or an audible sound. The history of activitymay be utilized to automatically connect communications from the user toa person with whom the user has prior interactions.

At 1112, at least a portion of the history of activities is delivered tothe first communication device. Such information may be used the user todetermine what items the user previously purchased. For example, theuser may wish to purchase the same item again or a related item, butdoes not remember the exact details of the item; or the user may wish toavoid purchasing the same item. The user may also use the information toidentify a person representing the organization with whom the userwishes to interact with again. For example, the user may have had apleasant experience with a given sales associate and know that salesassociate can meet the user's needs. In one embodiment, step 1112 is notperformed as part of process 1100.

Process 1100 may be used in conjunction with a loyalty program involvinglotteries or coupons that may be in existence before the communicationsplatform is implemented in the organization or may be created based onthe communications platform or a combination of the two.

FIG. 12 is a flowchart illustrating process 1200 for performingstructured communications in an observation platform in accordance withone embodiment of the present technology. Process 1200 may also bedescribed as disciplining communications in an observation platform. Inone embodiment, process 1200 is a computer implemented method that iscarried out by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 1200 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 1202, a signal is received from a first communication device or othercomputer system at a second communication device associated with acomputer system, wherein the signal comprises a mandatory message for athird communication device. For example, the mandatory message may be amessage that is required to be delivered to each employee associatedwith an organization and an acknowledgement must be received andrecorded. The requirement may be a legal requirement to notify employeesof certain information or may be requirement implemented by theorganization. The mandatory message may be delivered as an audiblemessage or a text message. The mandatory message may also direct a userto a location where more information may be found. In another example,the mandatory message may be a request for additional assistance for aspecific location or task, such as opening another cash register line orattending to shoppers needing mobile POS services.

At 1204, the signal is forwarded with the mandatory message to the thirdcommunication device associated with a user such that a receipt of themandatory message at the third communication device will lock featuresof the third communication device until the mandatory message has beenacknowledged by the user. For example, the third communication devicemay be a handheld device and may have features such as the ability tocommunicate with other devices or the ability to connect to otherdevices such as a computer system and may be used to access informationfrom a database. Upon receipt of the mandatory message, some or all ofthe features of the communication device may be locked or alteredmeaning that the user is not able to access the features or mustexperience a different behavior of the observation platform. Forexample, upon receipt of the mandatory message the communication devicemay lock, disable or alter the ability to communicate with otherdevices.

At 1206, an acknowledgement of the mandatory message is received fromthe third communication device at the second communication device. Theacknowledgement may be generated manually by the user of the thirdcommunication device or may be automatically generated. For example,upon receipt of the mandatory message, the third communication devicemay display an option to access the mandatory message. Once the useraccesses the message, the acknowledgement may be sent automatically, oran option may be presented to the user to send the message. In oneembodiment, the user is required to create an acknowledgement message oraction to send back. The acknowledgement message may be a text, buttonpress or audible message created by the user.

At 1208, the acknowledgement of the mandatory message is forwarded fromthe second communication device to the first communication device. Inone embodiment, the locked features of the third communication devicemay be unlocked in response to the user of the second communicationdevice accessing and/or acknowledging the mandatory message. In oneembodiment, the locked features of the third communication device may beunlocked in response the computer system receiving the action of thesecond communication device. In one embodiment, the locked or alteredfeatures of the third communication device may be modified in responseto the user of the first communication device receiving theacknowledgement or taking other action to drop the request.

At 1210, the signal with the mandatory message is forwarded to aplurality of communication devices associated with a plurality of userssuch that a receipt of the mandatory message at each of the plurality ofcommunication devices will lock or alter the features of each of theplurality of communication devices until the mandatory message has beenacknowledged by each of the plurality of users, if required, or a singleresponder, if required. The plurality of users in this case may befurther determined based factors such as responsibilities, roles,groupings, talents, interests, location and/or motion, or socialengagement factors. In one example, a request for additional help withcustomer POS and/or mobile POS (mPOS) may be initiated which might bedirected to a group of sales associates with contextual information suchas: qualified for register work, designated as a register support backup person at this time, located near the register or mPOS area needingassistance, and not currently in an engaged state. In this example, thealtered features may include the playing of messages or sounds in theear, activation of LEDs or screen displays or physical vibration.

At 1212, a characteristic of the forwarding the signal with themandatory message is tracked. In one embodiment, the system tracks thetime the message was sent, when it was heard by the user, and when andwhere the user was located when they acknowledged. Associated with thestatistical information is a speech file of what the user said. Thisfeature is ideal for communicating policy or liability information andassuring that that information was received and understood. It should beappreciated that there is more than one type or class of mandatorymessages. Each type or class may have different requirements for thedelivery and/or acknowledgement. In the case of the example above, thesystem might track such characteristics as: who responded, when (howquickly) they responded, where they responded, how they moved (speed anddirection), and how long it took them to arrive at the requiredlocation.

FIG. 13 is a flowchart illustrating process 1300 for structured trainingin an observation platform in accordance with one embodiment of thepresent technology. Process 1300 may also be described as discipliningcommunications in an observation platform. In one embodiment, process1300 is a computer implemented method that is carried out by processorsand electrical components under the control of computer usable andcomputer executable instructions. The computer usable and computerexecutable instructions reside, for example, in data storage featuressuch as computer usable volatile and non-volatile memory. However, thecomputer usable and computer executable instructions may reside in anytype of computer usable storage medium. In one embodiment, process 1300is performed by the components of FIG. 1A, 1B, 1C or 2. In oneembodiment, the methods may reside in a computer usable storage mediumhaving instructions embodied therein that when executed cause a computersystem to perform the method.

At 1302, a signal is received from a first communication device at asecond communication device associated with a computer system, wherein afirst characteristic of the signal corresponds to supplementalinformation useful for the instruction and the training. Additionalcharacteristics of the signal may include information indicative ageographic location of the first communication device, a characteristiccorresponding to an audible or sub-audible source, contextualinformation and environmental information. Moreover, a second signal maybe sent as part of the overall communication that contains theadditional characteristics. For example, the audible source may be thevoice of a user, the signal characteristics may include signal signatureinformation and contextual or environmental information may include userstatus (e.g., engaged, available or on-break) and/or background noiselevels or subaudible signals. The supplemental information may be usefulfor establishing and running a process for delivering information,alerts, instruction or a training module to an individual or group ofindividuals. The supplemental information may include informationrelated to a location determination, environmental surroundingsincluding audio and sub-audible information, user habits, useridentification, button presses, or other external influences of thesystem.

The first communication device may be a handheld device that is capableof sending and receiving signals and may comprise a display, amicrophone and a speaker. The first communication device may be owned byan organization and issued to the user or may be the user's personalproperty such as a smart phone executing an application. The secondcommunication device may be a radio base station as described herein maybe a second handheld device.

At 1304, a user associated with the first communication device isidentified at the computer system. The user may be identified as anemployee, manager, or other person employing the observation platform.The user may be identified by the user's name, a username, an employeenumber, a phone number, etc. The identity of the user may be employed toselect an appropriate training module in that is sent at step 1308. Forexample, there may be a list of training modules that the user isrequired to complete. The computer system may be tied to a database thattracks which training modules have been completed by the user and thusthe computer system may send a training module to the user that has notyet been completed.

At 1306, a status of the user is determined wherein the status comprisesa readiness of the user, at the computer system, based on thesupplemental information and information sent from the firstcommunication device to the second communication device. For example,the user may indicate to the computer system the status of the user. Theuser may indicate that she is available for training, or may indicatethat she is engaged, unavailable, or busy and should not receive atraining module. The user may manually indicate this status by pressingbuttons on the first communication device or by issuing voice commandsto the device. The computer system may also infer or determine that auser is busy based on the communication signals sent by thecommunication device associated with the user. For example, if the useris communicating with another device then the computer system may inferthat the user is busy and not available for training. In one embodiment,the user may schedule a time for training. For example, the user mayschedule training at the beginning of a work shift or a break period.

The geographic location of the user or the first communication devicemay be employed to determine which training module is to be sent to thedevice. For example, the user may be an associate or other user in aretail setting with multiple departments. The associate may be requiredto complete training modules associated with each of the departments.The computer system may determine that the associate is available fortraining and that the associated is located in the lumber department.The computer system may then determine that the training module for thelumber department should be sent to the first communication device.Moreover, the location of the user may indicate the user's availabilityfor training. For example, if an employee is located in a break roomthen it may be automatically determined that the employee is availablefor training.

At 1308, instructional information is sent to the first communicationdevice in response to a determination that the status of the userindicates a likelihood of readiness to receive the instructionalinformation, wherein the instructional information is for use by theuser in conjunction with the first communication device. Theinstructional information may be a training module or data on how a usermay obtain a training module. A training module may be instructionalinformation designed to teach or train the user. The instructions may berelated to the use and features of the first communication device in theobservation platform. The instructions may also be related to the user'seducation of information related to an organization employing theobservation platform. For example, the organization may be a retailsetting and the user is a sales associate. The training module may thenbe related to the policies and procedures of the retail setting orinformation regarding the products being sold. The training module maycomprise content that is audio, video, graphical, textual, or anycombination thereof. The content may be displayed or played using thefirst communication device. For example, the audio may be played intoheadphones connected to the first communication device worn by the user.Textual and other visual data may be displayed on a screen of the firstcommunication device.

The training module may be streamed to the user. In other words, thefirst communication device may not receive all of the content in onedownload or transmission. The first communication device may receive astream of data and display or play the stream of data as it is receivedwithout saving the data into storage at the device. In such an examplethe user may have the ability to pause, suspend or repeat the training.In one embodiment, the user may be available and begin a trainingmodule, but may become engaged or unavailable part way throughcompleting the training module. The user may indicate this status to thecomputer system and then resume the training module at a time when theuser is available again. The computer system may store the partialcompletion of the training module and where the user left off in thestream. The training module need not be streamed to the communicationdevice and may instead be downloaded to the communication device fromthe computer system or another data base. Alternatively, thecommunication device may be pre-loaded with training modules before itis employed by the user. The pre-loading or downloading may beaccomplished via well known techniques for transferring data between twonetworked electronic devices.

The training module may be described as an instructional audio stream,or audio “infomercials,” so that associates, supervisors, managers orother users can learn more about products, culture, brand identity orsystem usage. This training information can be distributed based onpriority and user location. For example a non-urgent product snippetmight only play when an employee enters the break room or the stockroom. Another type of training might be triggered by an employee nearinga certain area or object. A priority message might play whenever theemployee is not “engaged” with a shopper. Another way training“podcasts” can be heard is by the employee requesting a training streamvia speech command. In this case, the employee can hear the stream inthe background while going about her business and can suspend thetraining any time by pressing the “engaged” button.

The use of the training module may be described as a virtual trainingroom where detailed information can be delivered upon command orspecified actions. A button action such as engaged/interrupt wouldsuspend training if shoppers need assistance or a task needsconcentration. Users could call up new information, repeat informationor continue where they left off with older information. The TrainingRoom could also be a repository for manufacturer or brand-specificinformation. The retailer or a third party could sell space in thetraining room to the manufacturers for increasing brand awareness andknowledge. Analytics or tracking may indicate what was heard, when,where and by whom. Recommendations for learning could be associated withwhere associates spend their time, the context of communications or thegroups they are associated with. Contextual and location information isused to share relevant information with associates or others at theright time and place. The information or modules may be prioritized sothat the modules can play during the best times for the associates tohear it such as when they arrive or go on break. In another example,product training can be delivered to non-engaged associated in thevicinity of products, motivational information can be scheduled fordelivery at certain times of day, new feature introductions can bedelivered upon device authentication, management information can bedelivered to management groups, communication usage tips can bedelivered as employees enter the break room and motivational informationmight make use of changes in the social engagement quotient to determinewho should listen. Another example is that the retailer could sell earspace to manufacturers with differing values depending on the priorityand/or location with which it is delivered to the associates.

At 1310, the computer system tracking a use of the instructionalinformation in conjunction with the first communication device. Thecomputer system may be capable of tracking which users have completedtraining modules including the time and place the training modules werecompleted. Such information could be used by management in a retailsetting to determine which users are completing required training.Additionally, managers or others may use information to determine if thetraining modules are being used in the intended manner. For example, anemployee may always complete training modules in the same location andnot in the location they were intended to be completed in. Thus,observational metrics will show who hears what, where and when.Additionally, measurements of social engagement quotient or socialfactors may be compared before and after motivational or inspirationaltraining messages.

FIG. 14 is a flowchart illustrating process 1400 for monitoringcommunications in an observation platform in accordance with oneembodiment of the present technology. Process 1400 may also be describedas disciplining communications in an observation platform. In oneembodiment, process 1400 is a computer implemented method that iscarried out by processors and electrical components under the control ofcomputer usable and computer executable instructions. The computerusable and computer executable instructions reside, for example, in datastorage features such as computer usable volatile and non-volatilememory. However, the computer usable and computer executableinstructions may reside in any type of computer usable storage medium.In one embodiment, process 1400 is performed by the components of FIG.1A, 1B, 1C or 2. In one embodiment, the methods may reside in a computerusable storage medium having instructions embodied therein that whenexecuted cause a computer system to perform the method.

At 1402, at least one signal of a plurality of communication signals ismonitored via a computer system between a first communication device anda second communication device wherein a first characteristic of the atleast one signal corresponds to an audible source and a secondcharacteristic of the at least one signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may be the voice of a user, the signal characteristics mayinclude signal signature information and contextual or environmentalinformation and may include user status (e.g., engaged or on-break)and/or background noise levels. The first communication device may be ahandheld device that is capable of sending and receiving signals and maycomprise a display, a microphone and a speaker. The first communicationdevice may be owned by an organization and issued to the user or may bethe user's personal property such as a smart phone executing anapplication. The second communication device may be a radio base stationas described herein may be a second handheld device. It should beappreciated that the signal may actually be a plurality of signals. Forexample, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

The monitoring may be repeated or may occur simultaneously for aplurality of communication signals. Such signals may be from a pluralityof communication devices. For example, the first communication devicemay communicate with a plurality of other devices, or other devices notincluding the first communication device may all be communicating amultiple number of times within the observation platform. Process 1400may occur for a single signal or a plurality of signals.

At 1404, a determination is made that a user associated with the firstcommunication device is experiencing an issue with a feature of thefirst communication device. An issue may be defined to be any number ofdifficulties, errors, malfunctions, or other problems experienced by theuser who is using the first communication device. In one embodiment, theuser may not know how to properly use the device or all of its features.For example, the user may not know how to send a message, how to receivea message, how to send acknowledgements, how to change the volume, howto indicate a status of the user, etc. The user may or may not know thatthey are experiencing such an issue.

In one embodiment, the user may be under-utilizing the device by notusing all of the available features. For example, the user may not knowthat they are able to ask for assistance via the device, or may not knowwhat type of assistance that they may request. The computer system maydetermine that a user is in need of assistance based on one or morecharacteristics such as: the geographic location or a pattern ofgeographic locations of the user within a setting, motion and speed ofthe user, pattern of features used by the user, what the user has beenhearing and how they have or have not responded to hearing, button presspatterns, speech command patterns and changes in the social engagementfactors while using the device. The computer system may then determinethat the user is under-utilizing, over-utilizing or misusing the device.

In one embodiment, the computer may determine that the user isre-issuing the same commands to the device and determine that the resultdesired by the user has not been achieved. The computer system may thendetermine that a training module may assist the user in learning whichalternative commands may be issued to achieve the results desired by theuser. For example, the training module may teach the user specificphrases or actions that may be used to achieve desired results. Thetraining module may inform the user regarding the communications phrasesdescribed in process 300 herein. In other words, if the observationplatform monitors a user having difficulty with a command or function,it can automatically send a short audio script to the user withcorrective actions.

In one embodiment, the computer system determines or anticipates thatthe user is in need of tech support. The anticipation may be based oncommands issued to the device by the user, button presses or otheractions taken by the user, a geographic location of the user, speech totext conversion of audible portions of the signal with an algorithmsearching for key phrases in the text, an analysis of voice stress, orany combination thereof. The tech support may be offered in the form ofa training module or live audible support via the first communicationdevice in contact with a tech support representative. The tech supportfunction may be associated with the organization employing theobservation platform or may be provided through a third party.

At 1406, an invitation for a training module is sent from the computersystem to the first communication device, wherein the training module isfor use by the user in conjunction with the first communication device.The invitation to the device may be audible, textual, visual, or acombination thereof. The invitation may offer more than one trainingmodule options to the user. The user may then select the most relevantoption. Live tech support may also be offered to the user. The trainingmodules may instruct the user in how to use the communication device.The training modules may be similar to the training modules described inprocess 1300.

At 1408, the training module is sent to the first communication devicein response to receiving an acceptance of the invitation. For example,the user may audibly accept an invitation using key phrases. The keyphrases may be one of a list of key phrases that the computer systemwill recognize or may be given to the user with the invitation. In oneembodiment, the user presses a button on the first communication deviceto accept the invitation.

Process 1400 demonstrates how to use the observation platform to monitorhow users behave using the platform. The result of such monitoring canreduce field support costs and can even anticipate problems before theuser tries to make contact for support. User behavior monitoringimproves the product and software continuously and those improvementsmay then be shared with other observation platform users outside of theorganization which initially captured the user behavior. Theseimprovements may be offered as a service by those supplying theobservation platform to various organizations.

FIG. 15 is a flowchart illustrating process 1500 for mining data in anobservation platform in accordance with one embodiment of the presenttechnology. Process 1500 may also be described as discipliningcommunications in an observation platform. In one embodiment, process1500 is a computer implemented method that is carried out by processorsand electrical components under the control of computer usable andcomputer executable instructions. The computer usable and computerexecutable instructions reside, for example, in data storage featuressuch as computer usable volatile and non-volatile memory. However, thecomputer usable and computer executable instructions may reside in anytype of computer usable storage medium. In one embodiment, process 1500is performed by the components of FIG. 1A, 1B, 1C or 2. In oneembodiment, the methods may reside in a computer usable storage mediumhaving instructions embodied therein that when executed cause a computersystem to perform the method.

At 1502, at least one signal of a plurality of communication signals ismonitored via a computer system between a first communication device anda second communication device wherein a first characteristic of the atleast one signal corresponds to an audible source and a secondcharacteristic of the at least one signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may be the voice of a user, the signal characteristics mayinclude signal signature information and contextual or environmentalinformation may include user status (e.g., engaged or on-break) and/orbackground noise levels. The first communication device may be ahandheld device that is capable of sending and receiving signals and maycomprise a display, a microphone and a speaker. The first communicationdevice may be owned by an organization and issued to the user or may bethe user's personal property such as a smart phone executing anapplication. The second communication device may be a radio base stationas described herein may be a second handheld device. It should beappreciated that the signal may actually be a plurality of signals. Forexample, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

The monitoring may be repeated or may occur simultaneously for aplurality of communication signals. Such signals may be from a pluralityof communication devices. For example, the first communication devicemay communicate with a plurality of other devices, or other devices notincluding the first communication device may all be communicating amultiple number of times within the observation platform. Process 1400may occur for a single signal or a plurality of signals.

At 1504, classifications for data associated with the at least onesignal are identified. The classifications may or may not be related tofeatures or portions of the signal that are not the communicationitself. In other words, the communication itself may be an audible ortext message from one user to the other, but the communication alsocarries secondary data such as the time the communication was sent, orthe location of the device when the communication was sent, etc.

In one embodiment, the classifications are related to the non-messageportion of the communication and may comprise the time the message wassent, who sent the message, the length of the message, who the messagewas sent to, what the user listened to or heard, the length oflistening, the type of data in the message (i.e. audible, textual,etc.),

At 1506, the data and the classifications for the data are stored in adatabase. The data base may be part of the computer system or may bestored in another location accessible by the computer system. In oneembodiment the data base is a MySQL data base.

At 1508, a request is received, at the computer system, for a reportbased on the plurality of communication signals. The request maycomprise an inquiry or a request for a certain type of report. Forexample, the request may ask for the number of communications in theobservation platform for a given period of time for all devices withinthe platform. Or the request may be for all instances of communicationsfrom one user including the time, length, and to whom the communicationwas sent. Or the request may be for all communications between twousers. Or the request may be for a geographic location of a user priorto, during, or following communications from the user. Any number ofrequests may be made for a report based on the message and non-messageportions of the communications. Alternatively, the request may be sentto a hardware device associated with the observation platform other thanthe computer system that has access to the database.

At 1510, the report is generated based the data and the classifications.The report may comprise the message portion of the communication or onlynon-message data related to the communication that is generated based onthe classifications. The report can be generated to show the frequencyof communications from a user, or the frequency from one user to asecond user. Movements of a user or a group of users may be inferredbased on the location of the users prior to, during and following thecommunications. The report can separate what the user says to whom andwhat the user listens to and from what source. Such reports may beuseful to make inferences about user behavior. For example, in a retailsetting a manager or others may use the reports to infer that anassociate is located in an appropriate zone of the retail setting in agiven time frame and quickly responds to requests for assistance fromcustomers. Alternatively, a manager may infer that two given associatescommunicate too frequently with one another and during times that theyshould not be communicating. It should be appreciated that the varietyof reports that may be generated may be useful for a great number ofpurposes. In one embodiment, the reports are generated automatically inresponse to parameters established within the observation platform. Forexample, a computer system may be commanded to automatically produce adaily report for all communication associated with a given user. Thereport may be generated at the computer system and may be displayed atthe computer system and may be sent to another device.

FIG. 16 is a flowchart illustrating process 1600 for mining data in anobservation platform in accordance with one embodiment of the presenttechnology. Process 1600 may also be described as discipliningcommunications in an observation platform. In one embodiment, process1600 is a computer implemented method that is carried out by processorsand electrical components under the control of computer usable andcomputer executable instructions. The computer usable and computerexecutable instructions reside, for example, in data storage featuressuch as computer usable volatile and non-volatile memory. However, thecomputer usable and computer executable instructions may reside in anytype of computer usable storage medium. In one embodiment, process 1600is performed by the components of FIG. 1A, 1B, 1C or 2. In oneembodiment, the methods may reside in a computer usable storage mediumhaving instructions embodied therein that when executed cause a computersystem to perform the method.

At 1602, at least one signal of a plurality of communication signals ismonitored via a computer system between a first communication device anda second communication device wherein a first characteristic of the atleast one signal corresponds to an audible source and a secondcharacteristic of the at least one signal corresponds to informationindicative of a geographic position of the first communication device.Additional characteristics of the signal may include contextualinformation and environmental information. For example, the audiblesource may be the voice of a user, the signal characteristics mayinclude signal signature information and contextual or environmentalinformation may include user status (e.g., engaged, available oron-break) and/or background noise levels. The first communication devicemay be a handheld device that is capable of sending and receivingsignals and may comprise a display, a microphone and a speaker. Thefirst communication device may be owned by an organization and issued tothe user or may be the user's personal property such as a smart phoneexecuting an application. The second communication device may be a radiobase station as described herein may be a second handheld device. Itshould be appreciated that the signal may actually be a plurality ofsignals. For example, a first signal may be a transmission of the firstcharacteristic corresponding to the audible source and the second signalmay be the second characteristic corresponding to the informationindicative of geographic position of the first communication device.

The monitoring may be repeated or may occur simultaneously for aplurality of communication signals. Such signals may be from a pluralityof communication devices. For example, the first communication devicemay communicate with a plurality of other devices, or other devices notincluding the first communication device may all be communicating amultiple number of times within the observation platform. Process 1400may occur for a single signal or a plurality of signals.

At 1604, the audible source of the at least one signal is converted totext or other language recognized by a computer. Well known techniquesmay be employed for such a conversion. The audible portion of the signalmay be described as the message portion of the signal.

At 1606, the text is stored in a database. The data base may be part ofthe computer system or may be stored in another location accessible bythe computer system. In one embodiment the data base is a MySQL database.

At 1608, a request is received, at the computer system, for a reportbased on the plurality of communication signals. For example, a managerin a retail setting may request reports regarding communications ofassociates in the retail setting. The request may be for allcommunications involving a particular user. Or a request may be for allcommunications involving key phrases. For example, algorithms may beused to mine the text for the key phrase. A key phrase may be “lumber”and all communications involving the phrase “lumber” would then beincluded in the report. Automatic reports may be generated based onparameters established within the observation platform. Alternatively,the request may be sent to a hardware device associated with theobservation platform other than the computer system that has access tothe database.

At 1610, the report is generated based on the text. The report may begenerated at the computer system and may be displayed at the computersystem and may be sent to another device.

It should be appreciated that processes 300, 400, 500, 600, 700, 800,900, 1000, 1100, 1200, 1300, 1400, 1500 and 1600 need not carry out eachof the described steps to complete its operation. Nor do the steps needto be carried out in the order described. It should be appreciated thatprocesses 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300,1400, 1500 and 1600, or portions thereof, may be combined with oneanother using any number of combination. For example, the response fromthe computer system in process 800 may take place in 900, 1000, 1100 and1200.

FIGS. 17 and 18 are flowcharts illustrating processes 1700 and 1800 formediating data in an observation platform in accordance with oneembodiment of the present technology. Processes 1700 and 1800 may alsobe described as disciplining communications in an observation platform.In one embodiment, processes 1700 and 1800 are computer implementedmethods that are carried out by processors and electrical componentsunder the control of computer usable and computer executableinstructions. The computer usable and computer executable instructionsreside, for example, in data storage features such as computer usablevolatile and non-volatile memory. However, the computer usable andcomputer executable instructions may reside in any type of computerusable storage medium. In one embodiment, processes 1700 and 1800 areperformed by the components of FIG. 1A, 1B, 1C, 1D, or 2. In oneembodiment, the methods may reside in a computer usable storage mediumhaving instructions embodied therein that when executed cause a computersystem to perform the method.

At 1702, a first communication is parsed with a computer systemaccording to a policy to determine metadata associated with the firstcommunication, wherein the metadata comprises a first set of attributesand wherein the first communication is received at the computer systemfrom a first communication device. For example, first communication 104,computer system 120, policy 114, metadata 108, and device 105 of FIG. 1Dmay be employed.

At 1704, the first set of attributes is compared to attributes of aplurality of communication devices associated with the observationplatform, the comparing performed by the computing system. Such acomparison may employ a matching of attributes, use of attributeinhibitors, a voting system, or a combination thereof.

At 1706, at least one recipient communication device is identified fromthe plurality of communication devices for the first communication basedon the comparing, the identifying performed by the computing system.

At 1708, the first communication is relayed to the at least oneidentified recipient communication device via the computer system. Thismay also be described as forwarding the message and may occur insubstantially real time. In one embodiment, the first communication isautomatically played at the recipient communication device once it isreceived. The recipient device may respond to the first communicationwith a second communication as is described in process 1800.

At 1802, a second communication is received from the at least oneidentified recipient communication device at the computer system. Thesecond communication device may be device 110 of FIG. 1D.

At 1804, the second communication is parsed with the computer systemaccording to the policy to determine metadata associated with the secondcommunication.

At 1806, the second communication is identified as a response to thefirst communication based on the metadata.

At 1808, the second communication is relayed to the first communicationdevice in response to the identifying the second communication as theresponse.

FIG. 19 is a flowchart illustrating process 1900 for using anobservation platform to measure and quantify social skills in accordancewith one embodiment of the present technology. In one embodiment,process 1900 shows computer implemented methods that are carried out byprocessors and electrical components under the control of computerusable and computer executable instructions. The computer usable andcomputer executable instructions reside, for example, in data storagefeatures such as computer usable volatile and non-volatile memory.However, the computer usable and computer executable instructions mayreside in any type of computer usable storage medium. In one embodiment,process 1900 is performed by the components of FIG. 1A, 1B, 1C, 1D, or2. In one embodiment, the methods may reside in a computer usablestorage medium having instructions embodied therein that when executedcause a computer system to perform the method.

At 1902, communications between at least two devices are intercepted andrelayed by a computer system wherein a portion of the communicationscorrespond to an audible source and wherein the relaying thecommunications is based on context information derived from thecommunications by the computer system. In other words, the observationplatform is employed for intercepting a communication and determiningthe destination to relay the communication to. The relaying may alsoemploy metadata and policies as described herein. In one embodiment, thecommunications comprise information indicative of geographic location orposition. This information may be the location data itself or may beinformation that allows the computer system to infer the location. Itshould be appreciated that a single communication may be sent using onesignal may be split into a plurality of signals. For example, a firstsignal may be a transmission of data pertaining to an audible source andthe second signal may be information indicative of a geographic locationor other additional information.

At 1904, Primary Statistics are measured based on the communications atthe computer system. For example, the computer system may be computer120 of FIG. 1A. The Primary Statistics may be data related to: engagedor available time(s), locations, locations traversed including speed anddirection, listen time, talk time, number of listeners, geographiclocation of the speakers and listeners, type of communication (e.g.,broadcast, private conversations, interruptions, group conversations,announcements, interrupting announcements, mandatory response messages),length of the communication session, initiator of communications,receiver of communications, presence information, keywords spoken orlistened to, tone of voice, speech cadence, banter rate, emotion andinflection (as measured by voice stress analysis tools), lengths ofspeech segments, what policies are used for the communications, when andwhere two or more individuals dwell in close proximity to each other orto specific locations, the speed of movement and pausing of thelistening individuals during/after talking or listening, the frequencythat listeners delay hearing a message or drop out from what a speakeris saying, and/or promptness of responses to what was heard, InertialMeasurement Unit (IMU) data, radio signal strength (RSS), signal tonoise ratio (SINR), measurements from accelerometer, and (X,Y,Z)location coordinates

At 1906, Secondary Statistics are generated related to a user associatedwith one of the at least two devices to generate an assessment of theuser wherein the Secondary Statistics quantify social skills of theuser. The Secondary Statistics and assessment quantify the sociabilitypotential and social factors of the user and conveys an ability and/orwillingness of the user to communicate as described herein in referenceto FIG. 1A. In one embodiment, the Secondary Statistics are generatedusing inference rules and weighted sums. An inference rule may bechanged or tuned during the generation of Secondary Statistics. ThePrimary Statistics may be sent to a second computer system to generatethe Secondary Statistics using cloud computing techniques.

In one embodiment, the Secondary Statistics also are based on externalstatistics such as: length of employment, languages spoken, jobidentity, employment hours, location assignments, skills possessed,desired skills, roles, responsibilities or social engagement quotient(SEQ). In one embodiment, the assessment is dynamically updated based onnew communications between the two devices.

It should be appreciated that process 1900 may generate an assessmentand Secondary Statistics for a single user or for a plurality of users.The plurality of users may be a related group such as all employeesassociated with a retail environment or all employees in a retailenvironment during a shift.

At 1908, the assessment is made available to a third party which may bea person, a plurality of people or a computer system. The assessment maybe used by the third party or others to make decisions for combininggroups of users into teams.

At 1910, a visual representation is generated based on the assessmentthat maps information from the assessment to geographical or logicalmaps, graphs or spatial representations. For example, the visualrepresentation may be a map that shows the geographic location of a userover a period of time within the retail environment. Thus the visualrepresentation may convey where an employee spends their time while onshift and where the employee is located when communicating or engagedwith shoppers. The visual representation may also depict the types ofcommunications that are made in certain areas. For example, it may showthat an employee will answer communications even when in the break room.Or the visual representation may show that two employees are likely toonly communicate with each other during certain times or in certainplaces.

FIG. 20 is a flowchart illustrating process 2000 for using structuredcommunications to validate a hypothesis related to social skills andsocial factors in accordance with one embodiment of the presenttechnology. In one embodiment, process 2000 is computer implementedmethods that are carried out by processors and electrical componentsunder the control of computer usable and computer executableinstructions. The computer usable and computer executable instructionsreside, for example, in data storage features such as computer usablevolatile and non-volatile memory. However, the computer usable andcomputer executable instructions may reside in any type of computerusable storage medium. In one embodiment, process 2000 is performed bythe components of FIG. 1A, 1B, 1C, 1D, or 2. In one embodiment, themethods may reside in a computer usable storage medium havinginstructions embodied therein that when executed cause a computer systemto perform the method.

At 2002, a hypothesis of key elements of social skills or social factorswhich are characteristic of the desired set of social factors needed forthe role or position are received at a computer system. The hypothesismay be created by a manager, a plurality of mangers, other individualsor plurality of individuals or may be automatically generated by amachine such as the computer system. The hypothesis may also begenerated by the manager or others and supplemented or modified by amachine. In one embodiment, the hypothesis is created by the managerbased on experience, judgment, and/or the input of a consultant as towhat social skills or sociability potential of employees are needed fora given shift or other assignment to meet the set of defined goals. Thehypothesis is then tested using the following steps. The defined set ofgoals may be financial such as achieving a specified level of sales in aretail environment.

Steps 2004, 2006 and 2008 are similar to steps 1902, 1904 and 1906 ofprocess 1900 and comprise the same features, capabilities andlimitations.

At 2004, communications between at least two devices are intercepted andrelayed by a computer system wherein a portion of the communicationscorrespond to an audible source and wherein the relaying thecommunications is based on context information derived from thecommunications by the computer system.

At 2006, Primary Statistics are measured based on the communications atthe computer system.

At 2008, Secondary Statistics are generated related to a user associatedwith one of the at least two devices to generate an assessment of theuser wherein the Secondary Statistics quantify the social skills.

At 2010, the hypothesis is validated at the computer system based on acomparison of the Secondary Statistics to the key element or socialfactors which are characteristic of the desired set of social factorsneeded for the role or positions. The validation could be that thehypothesis is valid or not valid. In one embodiment, the hypothesis isfound not valid but is improved via input from the manager, relevantindividuals or the computer system. The improved hypothesis may then bevalidated or not. The input for the improved hypothesis may be to tunean inference rule for generating the Secondary Statistics. Thevalidation step is used to provide the manager or others withinformation as to whether the hypothesis is useful making decisions into obtain the defined set of goals.

The following is an example of how process 2000 may be implemented.Store chain ABC has several stores in different regions. Each store isopen an average of 12 hours a day, more on Wednesdays and Saturdays,less on Sundays. The management has deployed the observation platform,and is sophisticated in the use of big data and data analytics. Themanagement now is embarking on use of the observation platform toimprove shift scheduling and hiring. This program will consist of thefollowing phases:

Phase 0: Management has already defined a set of goals for employeecosts, unit sales, and certain specific sales goals in new productcategories.

Phase 1: Management uses its own experience and expert judgment, withexternal consultants, to hypothesize key elements of employee behaviorneeded for plan success, and how this behavior can be measured.Management verifies that the observation platform will be configuredusing the internal set-up tools, parameters, policy selection, andinformation selection tools to gather the needed Primary Statisticswhile providing the communication, location and contextual support thatis inherent to the observation platform.

Phase 2: Management lays in place the analytics program to producebehavioral metrics based on the hypothesis, and to compare those metricswith the observed store results to validate, discard, and improve thevarious hypothesis. Management also recognizes that there may be otherrelations not obvious to them, and elects to use the machine-generatedhypothesis to look further into other factors that might contribute tosuccess.

Phase 3: Management begins to execute the new program, tuning theinference rules using by comparing higher level statistics againstresults, both manually to generate insight and in the machine toleverage the power of big data.

Phase 4: Management uses the discovered rules in a set of modelingactivities to assist in optimizing staffing, and to improve hiring,training, and incentives for both employees and immediate storesupervision.

Continuing Phase: At the same time, management continues with theactivities initiated in the earlier phases to build a system ofcontinuous improvement. Through the continuous improvement enabled byall Information Technology and especially by the Observation Platform,management is able to be agile in tracking market trends and productopportunities, and continues advancing in retail leadership.

Phase 1 may further comprise:

Management believes that ‘team relationships’ are fundamental.Management expects to find that employee groups of ‘loners’ and ‘teamplayers’, and that the likely program will be to identify the best teamplayers, allocate them at the most leveraged times, while moving theloners to less leveraged times and modifying HR policies to get moreteam players while reducing the number of the loners. Management alsobelieves that teaming may be fundamentally driven by certain keygroupings or partnerships, and that discovering these naturalpartnerships will help in assigning shift schedules. Management expectsto divide the team players into distinct categories: “Amiables” havingan easy and often-used facility to interact and greet, “Helpers” havinga proclivity to respond to requests but not necessarily to initiate aninteraction, “Experts” having deep knowledge as evinced by being thetarget of certain types of interactions from others, and “Managers” asmeasured by a likelihood of organizing tasks including customer-help.Management expects to find that high-performing teams will be made ofsome appropriate mix of these types and that the identified ‘loners’will negatively impact performance. Management builds a table thatsummarizes these expectations, using this to guide the programming ofthe observation platform and the analytics derived from the platform.Finally, management enables the sophisticated auto-search for rule' inthe analytics to see what other patterns might emerge by certain cannedalgorithmic procedures that themselves generate algorithmic proceduresin order to look for emergent higher order statistics casuallyassociated with store performance under various times and schedules.(Some team make-up might be better for the ‘shopper-gatherer, morefemale’ week-day crowd vs the ‘hunter-purchaser, more male’ Saturday andevening crowd).

Phase 2 may further comprise:

Management rolls out the program, and the Observation Platform gathersthe Primary Statistics.

Phase 3 may further comprise:

The Analytics Platform, using the Primary Statistics from theObservation Platform, groups employees into the categories defined bymanagement, and then correlates different mixes with the historicalstore results. This reveals that the Mgmt and Helper categories are lesscorrelated with success, and that the Amiable and Expert are morestrongly correlated. Additionally, the analytics platform varies thestrengths of the couplings (as in the above table), adjusting theweights to optimize the predictiveness of the higher-level statistics,also called behavioral metrics.

FIG. 21 is a flowchart illustrating process 2100 for using anobservation platform to measure and quantify social skills in accordancewith one embodiment of the present technology. In one embodiment,process 2100 is computer implemented methods that are carried out byprocessors and electrical components under the control of computerusable and computer executable instructions. The computer usable andcomputer executable instructions reside, for example, in data storagefeatures such as computer usable volatile and non-volatile memory.However, the computer usable and computer executable instructions mayreside in any type of computer usable storage medium. In one embodiment,process 2000 is performed by the components of FIG. 1A, 1B, 1C, 1D, or2. In one embodiment, the methods may reside in a computer usablestorage medium having instructions embodied therein that when executedcause a computer system to perform the method.

At 2102, at least a first set of data and a second set of data arecollected at a computer system from at least one device wherein thefirst set of data comprises a constant flow of data pertaining togeographic locations of the at least one device. The second set of datamay be context data or information derived from communications from thefirst device, intercepted at the computer system and relayed to a seconddevice. The second set of data may be other data gathered by thecomputer system.

At 2104, Primary Statistics and metrics are generated at the computersystem from first the first set of data and the second set of data.

At 2106, Secondary Statistics are generated related to a user associatedthe at least one device to generate an assessment of the user whereinthe Secondary Statistics quantify social behaviors of the user.

At 2108, the assessment is made available to a third party.

FIG. 22 is a flowchart illustrating process 2200 for using anobservation platform to measure and quantify social skills in accordancewith one embodiment of the present technology. In one embodiment,process 2200 is computer implemented methods that are carried out byprocessors and electrical components under the control of computerusable and computer executable instructions. The computer usable andcomputer executable instructions reside, for example, in data storagefeatures such as computer usable volatile and non-volatile memory.However, the computer usable and computer executable instructions mayreside in any type of computer usable storage medium. In one embodiment,process 2200 is performed by the components of FIG. 1A, 1B, 1C, 1D, or2. In one embodiment, the methods may reside in a computer usablestorage medium having instructions embodied therein that when executedcause a computer system to perform the method.

It should be appreciated that that process 2200 is accomplished usingdevices and computer systems associated with an observation platform.The observation platform may be for a retail environment or otherenvironment where an observation platform may be used.

In one embodiment, device statistics 2202, communications statistics2204, and computer system statistics 2206 are all input data that isgenerated by the observation platforms with their devices and componentsas described in FIGS. 1A, 1B, 1C, 1D, and 2. Device statistics 2202 maybe statistics related to a handheld device in a retail environment suchas a smart phone. In one embodiment, device statistics 2202 isinformation indicative of a geographic location of the device.Communications statistics 2204 may be statistics related tocommunications between two devices such as is described herein. Thecommunications statistics 2204 may be based on the actual text of thecommunication after the communication has been converted from voice totext or may be based on the characteristics of the communication such aswhen it was sent, who sent it, who receive it, etc. Computer systemstatistics 2206 may be related to the statistics or data stored in acomputer system associated with the observation platform and may includedata similar to 2202 and 2204.

At 2208, the device statistics 2202, communications statistics 2204, andcomputer system statistics 2206 inputted into or collected by theobservation platform. This may be accomplished by a first computersystem associated with the observation platform.

At 2210, the first computer system receives an input of data from othersystems such as data from a finance department, a human resourcesdepartment, or other department associated with the environment in whichin the observation platform is used.

At 2212, the first computer system is employed to derive SecondaryStatistics based on 2202, 2204, 2206, and/or 2210. The SecondaryStatistics may be the same as described in processes 1900, 2000 and2100.

At 2214, reports may be published based on the Secondary Statistics.Such reports may be made available to a manager or other personassociated with the observation platform. The report may include text,graphs, and other forms of present data.

At 2216, the first computer system receives an input of data from othersystems such as data from a finance department, a human resourcesdepartment, or other department associated with the environment in whichin the observation platform is used.

At 2218, the first computer system is employed to generate a sociabilityengagement quotient (SEQ) based on the Secondary Statistics and theinput from 2216.

At 2220, reports may be published based on the SEQ. Such reports may bemade available to a manager or other person associated with theobservation platform. The report may include text, graphs, and otherforms of present data.

At 2222, the SEQ may be outputted to a computer system that may or maynot be associated with the observation platform. The SEQ may then beemployed for a variety of purposes including creating schedules ofpersonnel, the placement of personnel in roles, or for scripted trainingmessages appropriate to the SEQ at that time.

At 2224, historical store data is inputted into the first computersystem. The store may be a retail environment associated with theobservation platform. The store may also refer to another type ofenvironment associated the observation platform. The historical storedata may be past data pertaining to 2202, 2204, 2206, or may be pastdata related to 2210 or 2216, or may be past Secondary Statistics orpast SEQ's.

At 2226, the first computer system is employed to derive a shift SEQ andcorrelate the historical store data. The shift SEQ may be an SEQ basedon Secondary Statistics that relates only to a shift for a retailenvironment. For example, the shift may refer to a given amount of timewhen the retail environment had a staff of employing working. The shiftSEQ may be based only on the employees working during the shift.

At 2228, the shift SEQ and/or other SEQ's are outputted into workforcescheduling for use in making decisions. The decisions may be todetermine which employees to staff during particular future shifts.

At 2230, the shift SEQ from 2226 and/or the output from 2228 areemployed to generate predictive modeling of store performance at thefirst computer system. The predictive modeling may refer to predictivesuccess of a store such as sales records, etc.

Example Computer System Environment

Portions of the present technology are composed of computer-readable andcomputer-executable instructions that reside, for example, incomputer-usable media of a computer system or other user device.Described below is an example computer system or components that may beused for or in conjunction with aspects of the present technology.

It is appreciated that that the present technology can operate on orwithin a number of different computer systems including general purposenetworked computer systems, embedded computer systems, cloud-basedcomputers, routers, switches, server devices, user devices, variousintermediate devices/artifacts, stand-alone computer systems, mobilephones, personal data assistants, televisions and the like. The computersystem is well adapted to having peripheral computer readable media suchas, for example, a floppy disk, a compact disc, and the like coupledthereto.

The computer system includes an address/data bus for communicatinginformation, and a processor coupled to bus for processing informationand instructions. The computer system is also well suited to amulti-processor or single processor environment and also includes datastorage features such as a computer usable volatile memory, e.g. randomaccess memory (RAM), coupled to bus for storing information andinstructions for processor(s).

The computer system may also include computer usable non-volatilememory, e.g. read only memory (ROM), as well as input devices such as analpha-numeric input device, a mouse, or other commonly used inputdevices. The computer system may also include a display such as liquidcrystal device, cathode ray tube, plasma display, and other outputcomponents such as a printer or other common output devices.

The computer system may also include one or more signal generating andreceiving device(s) coupled with a bus for enabling the system tointerface with other electronic devices and computer systems. Signalgenerating and receiving device(s) of the present embodiment may includewired serial adaptors, modems, and network adaptors, wireless modems,and wireless network adaptors, and other such communication technology.The signal generating and receiving device(s) may work in conjunctionwith one or more communication interface(s) for coupling information toand/or from the computer system. A communication interface may include aserial port, parallel port, Universal Serial Bus (USB), Ethernet port,antenna, or other input/output interface. A communication interface mayphysically, electrically, optically, or wirelessly (e.g. via radiofrequency) couple the computer system with another device, such as acellular telephone, radio, a handheld device, a smartphone, or computersystem.

Although the subject matter is described in a language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

What is claimed:
 1. A method for using an observation platform tomeasure and quantify social skills, comprising: intercepting andrelaying, at a computer system, communications between at least twodevices wherein a portion of said communications correspond to anaudible source and wherein said relaying said communications is based oncontext information derived from said communications by said computersystem; measuring primary statistics based on said communications atsaid computer system; generating secondary statistics related to a userassociated with one of said at least two devices to generate anassessment of said user wherein said secondary statistics quantifysocial behaviors of said user; and making said assessment available to athird party.
 2. The method as recited in claim 1 wherein said thirdparty is selected from the group of third parties consisting of aperson, a plurality of persons, and a second computer system.
 3. Themethod as recited in claim 1 wherein said comprise informationindicative of a geographic location of one of said two devices andwherein said computer system infers said geographic location of said oneof said two devices based on said information.
 4. The method as recitedin claim 1 wherein said generating said secondary statistics isaccomplished using an inference rule with an algorithm to construct aweighted sum based on data associated with said primary statistics. 5.The method as recited in claim 1 wherein said assessment furthercomprises high order statistics generated through an application of aninference rule to said secondary statistics.
 6. The method as recited inclaim 1 wherein said communications are relayed an observation platformand said secondary statistics are based on data from said observationplatform and from data generated outside of said observation platform.7. The method as recited in claim 1 wherein said assessment is for useby said third party in making decisions for combining groups of usersinto teams.
 8. The method as recited in claim 1 wherein said assessmentis for use by a related computer system or other non-human device usedto signal, control, supervise, quantify, analyze or otherwise utilizethe assessment information.
 9. The method as recited in claim 1 whereinsaid assessment quantifies metrics that conveys an ability andwillingness of said user to communicate, educate, or engage with others.10. The method as recited in claim 1 wherein said assessment is relatedto a group of users.
 11. The method as recited in claim 1 wherein saidassessment is dynamically updated based on new secondary statisticsbased on new primary statistics.
 12. The method as recited in claim 1wherein said devices and said computer system are associated with aretail environment.
 13. The method as recited in claim 1 wherein saidprimary statistics are selected from the group of primary statisticsconsisting of: engagement time, available times, location maps, talktime, listen time, number of listeners, geographic location of device,locations traversed including speed and direction, length of saidcommunication, under what circumstances, who initiated communications towhich groups and individuals, presence information, type ofcommunication, key words, keywords spoken or listened to, tone, emotion,lengths of speeches, lengths of speech segments, what policies are usedfor the communications, when and where two or more individuals dwell inclose proximity to each other or to specific locations, speed ofmovement and pausing of listening individuals during/after talking orlistening, and frequency that listeners delay hearing a message or dropout from what a speaker is saying, and/or promptness of responses towhat was heard.
 14. The method as recited in claim 1 further comprising:generating a visual representation based on said assessment that mapsinformation from said assessment geographical or logical maps, graphs orspatial representations.
 15. The method as recited in claim 1 whereinsaid assessment is combined with external statistics selected from thegroup of external statistics consisting of: length of employment,languages spoken, job identity, employment hours, location assignments,skills possessed, desired skills, roles, responsibilities, and socialengagement quotient (SEQ).
 16. The method as recited in claim 1 whereina communication of said communication sent from one of said at least twodevices via a plurality of signals.
 17. A non-transitory computer-usablestorage medium having instructions embodied therein that when executedcause a computer system to perform a method for using structuredcommunications to quantify social skills, said method comprising:intercepting and relaying, at a computer system, communications betweenat least two devices wherein a portion of said communications correspondto an audible source and wherein said relaying said communications isbased on context information derived from said communications by saidcomputer system; measuring primary statistics based on saidcommunications at said computer system; generating secondary statisticsrelated to a user associated with one of said at least two devices togenerate an assessment of said user wherein said secondary statisticsquantify social behaviors of said user; and making said assessmentavailable to a third party.
 18. The non-transitory computer-usablestorage medium as recited in claim 17 wherein said third party isselected from the group of third parties consisting of a person, aplurality of persons, and a second computer system.
 19. Thenon-transitory computer-usable storage medium as recited in claim 17wherein said communications comprise information indicative of ageographic location of one of said two devices and wherein said computersystem infers said geographic location of said one of said two devicesbased on said information.
 20. The non-transitory computer-usablestorage medium as recited in claim 17 wherein said generating saidsecondary statistics is accomplished using an inference rule with analgorithm to construct a weighted sum based on data associated with saidprimary statistics.
 21. The non-transitory computer-usable storagemedium as recited in claim 17 wherein said assessment further compriseshigh order statistics generated through an application of an inferencerule to said secondary statistics.
 22. The non-transitorycomputer-usable storage medium as recited in claim 17 wherein saidcommunications are relayed via an observation platform and saidsecondary statistics are based on data from said observation platformand from data generated outside of said observation platform.
 23. Thenon-transitory computer-usable storage medium as recited in claim 17wherein said assessment is for use by said third party in makingdecisions for combining groups of users into teams.
 24. Thenon-transitory computer-usable storage medium as recited in claim 17wherein said assessment quantifies metrics that conveys a measurement ofan ability and willingness of said user to communicate.
 25. Thenon-transitory computer-usable storage medium as recited in claim 17wherein said assessment is related to a group or plurality of groups ofusers.
 26. The non-transitory computer-usable storage medium as recitedin claim 17 wherein said assessment is dynamically updated based on newsecondary statistics based on new communications.
 27. The non-transitorycomputer-usable storage medium as recited in claim 17 wherein said twodevices and said computer system are associated with a retailenvironment.
 28. The non-transitory computer-usable storage medium asrecited in claim 17 wherein said primary statistics are selected fromthe group of primary statistics consisting of: engagement time,available times, location maps, talk time, listen time, number oflisteners, geographic location of device, locations traversed includingspeed and direction, length of said communication, under whatcircumstances, who initiated communications to which groups andindividuals, presence information, type of communication, key words,keywords spoken or listened to, tone, emotion, lengths of speeches,lengths of speech segments, what policies are used for thecommunications, when and where two or more individuals dwell in closeproximity to each other or to specific locations, speed of movement andpausing of listening individuals during/after talking or listening, andfrequency that listeners delay hearing a message or drop out from what aspeaker is saying, and/or promptness of responses to what was heard. 29.The non-transitory computer-usable storage medium as recited in claim 17further comprising: generating a visual representation based on saidassessment that maps information from said assessment to geographical orlogical maps, graphs, or spatial representations.
 30. The non-transitorycomputer-usable storage medium as recited in claim 17 wherein saidassessment is combined with external statistics selected from the groupof external statistics consisting of: length of employment, languagesspoken, job identity, employment hours, location assignments, skillspossessed, desired skills, roles, responsibilities, and socialengagement quotient (SEQ).
 31. The non-transitory computer-usablestorage medium as recited in claim 17 wherein a communication of saidcommunication sent from one of said at least two devices via a pluralityof signals.
 32. An observation platform for using structuredcommunications to generate statistics, comprising: a plurality ofdevices for sending and receiving communications; and a computer systemfor: intercepting and relaying said communications between saidplurality of devices wherein a portion of said communications correspondto an audible source and wherein said relaying said communications isbased on context information derived from said communications by saidcomputer system; measuring primary statistics based on saidcommunications; generating secondary statistics related to a userassociated with one of said plurality of devices to generate anassessment of said user wherein said secondary statistics quantifysocial behaviors of said user; and making said assessment available to athird party.
 33. The observation platform as recited in claim 32 whereinsaid third party is selected from the group of third parties consistingof a person, a plurality of persons, and a second computer system. 34.The observation platform as recited in claim 32 wherein saidcommunications comprise information indicative of a geographic locationof one of said plurality of devices and wherein said computer systeminfers said geographic location of said one of said two devices based onsaid information.
 35. The observation platform as recited in claim 32wherein said generating said secondary statistics is accomplished usingan inference rule with an algorithm to construct a weighted sum based ondata associated with said primary statistics.
 36. The observationplatform as recited in claim 32 wherein said assessment quantifiesmetrics that conveys an ability and willingness of said user tocommunicate.
 37. The observation platform as recited in claim 32 whereinsaid primary statistics are selected from the group of primarystatistics consisting of: engagement time, available times, locationmaps, talk time, listen time, number of listeners, geographic locationof device, locations traversed including speed and direction, length ofsaid communication, under what circumstances, who initiatedcommunications to which groups and individuals, presence information,type of communication, key words, keywords spoken or listened to, tone,emotion, lengths of speeches, lengths of speech segments, what policiesare used for the communications, when and where two or more individualsdwell in close proximity to each other or to specific locations, speedof movement and pausing of listening individuals during/after talking orlistening, and frequency that listeners delay hearing a message or dropout from what a speaker is saying, and/or promptness of responses towhat was heard.